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Refine results</h3>
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Year</div>
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2009
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<span class="floatL">(98)</span>
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</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_35302031100">
Kaiser, C.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(9)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="35302031100" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="6603957531" id="cat_6603957531" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_6603957531">
Bodendorf, F.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(9)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="6603957531" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="35615668400" id="cat_35615668400" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_35615668400">
Kazienko, P.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(9)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="35615668400" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="7004187647" id="cat_7004187647" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_7004187647">
Alhajj, R.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(9)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
										<input value="selectedAuthorClusterCategories" type="hidden">
<input value="7004187647" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="7403590865" id="cat_7403590865" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_7403590865">
Wu, B.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(9)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="7403590865" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_AUTHOR_NAME_AND_ID">
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="8717221100" id="cat_8717221100" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_8717221100">
Ting, I.H.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(8)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="8717221100" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="24460475800" id="cat_24460475800" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_24460475800">
Lin, S.D.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(8)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="24460475800" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="35110976200" id="cat_35110976200" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_35110976200">
Brodka, P.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(7)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="35110976200" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="7405918429" id="cat_7405918429" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_7405918429">
Wang, B.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(7)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="7405918429" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAuthorClusterCategories" value="12778641000" id="cat_12778641000" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_12778641000">
Dawson, S.
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(6)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAuthorClusterCategories" type="hidden">
<input value="12778641000" type="hidden">
</span>
 			
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsAuthnameCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','AUTHOR_NAME_AND_ID','selectedAuthorClusterCategories','12');" title="View more" id="viewMoreLink_AUTHOR_NAME_AND_ID">
View more</a>
<span id="viewDivider_AUTHOR_NAME_AND_ID" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('AUTHOR_NAME_AND_ID');" title="View fewer" id="viewFewerLink_AUTHOR_NAME_AND_ID" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_AUTHOR_NAME_AND_ID" class="displayNone navigatorOverlay">
<div id="overlayLoading_AUTHOR_NAME_AND_ID" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_2">
<div class="floatL">
Author Name 
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('AUTHOR_NAME_AND_ID');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_AUTHOR_NAME_AND_ID">
<ul class="refineResults floatL overlayUL" id="overlayul_AUTHOR_NAME_AND_ID1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AUTHOR_NAME_AND_ID2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AUTHOR_NAME_AND_ID3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AUTHOR_NAME_AND_ID4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_AUTHOR_NAME_AND_ID" class="displayNone"><li></li></ul>
<div id="overlayFooter_AUTHOR_NAME_AND_ID" class="displayNone">
<div class="floatR txtSmaller marginR8">
Sort on:
<select name="scla" onchange="handleClusterSorting('resultslist','b','AUTHOR_NAME_AND_ID','selectedAuthorClusterCategories')" id="clusterSort_scla"><option selected="selected" value="# of results"># of results</option>
<option value="A">A</option>
<option value="B">B</option>
<option value="C">C</option>
<option value="D">D</option>
<option value="E">E</option>
<option value="F">F</option>
<option value="G">G</option>
<option value="H">H</option>
<option value="I">I</option>
<option value="J">J</option>
<option value="K">K</option>
<option value="L">L</option>
<option value="M">M</option>
<option value="N">N</option>
<option value="O">O</option>
<option value="P">P</option>
<option value="Q">Q</option>
<option value="R">R</option>
<option value="S">S</option>
<option value="T">T</option>
<option value="U">U</option>
<option value="V">V</option>
<option value="W">W</option>
<option value="X">X</option>
<option value="Y">Y</option>
<option value="Z">Z</option>
<option value="Undefined">Undefined</option></select>
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','AUTHOR_NAME_AND_ID','selectedAuthorClusterCategories','12');" title="View more" id="vmore_AUTHOR_NAME_AND_ID">
View more</a>
<span id="divider_AUTHOR_NAME_AND_ID">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('AUTHOR_NAME_AND_ID');" title="View fewer" id="vfew_AUTHOR_NAME_AND_ID">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_3" class="dummyNav zoomFix" lang="cat_SUBJAREA">
<span id="checkArray_SUBJAREA" class="displayNone"></span>
<div id="heading_SUBJAREA" class="scopusClusterHeader ">
<div class="dragDropBox moveCursor">
Subject Area</div>
<div id="collapse_SUBJAREA" class="clickBox">
<span class="btn_collapse" title="Click to close" onclick="collapseSection('SUBJAREA','collapse')">&nbsp;</span>
</div>
<span id="checkCount_SUBJAREA" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody " id="body_SUBJAREA">
<div id="viewMoreCount_SUBJAREA" class="displayNone">5</div>
<div id="viewLessCount_SUBJAREA" class="displayNone">0</div>
<div id="totalClusterCount_SUBJAREA" class="displayNone">11</div>
<ul class="refineResults txtSmaller" id="cluster_SUBJAREA">
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="COMP" id="cat_COMP" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_COMP">
Computer Science
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(941)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="COMP" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="ENGI" id="cat_ENGI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_ENGI">
Engineering
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(227)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="ENGI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="SOCI" id="cat_SOCI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_SOCI">
Social Sciences
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(186)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="SOCI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="MATH" id="cat_MATH" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_MATH">
Mathematics
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(163)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="MATH" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="BUSI" id="cat_BUSI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_BUSI">
Business, Management and Accounting
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(104)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="BUSI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_SUBJAREA">
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="DECI" id="cat_DECI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_DECI">
Decision Sciences
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(80)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="DECI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="PSYC" id="cat_PSYC" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_PSYC">
Psychology
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(28)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="PSYC" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="MEDI" id="cat_MEDI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_MEDI">
Medicine
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(18)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="MEDI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="EART" id="cat_EART" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_EART">
Earth and Planetary Sciences
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(17)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="EART" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSubjectClusterCategories" value="ENVI" id="cat_ENVI" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_ENVI">
Environmental Science
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(13)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSubjectClusterCategories" type="hidden">
<input value="ENVI" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsSubareaCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','SUBJAREA','selectedSubjectClusterCategories','11');" title="View more" id="viewMoreLink_SUBJAREA">
View more</a>
<span id="viewDivider_SUBJAREA" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('SUBJAREA');" title="View fewer" id="viewFewerLink_SUBJAREA" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_SUBJAREA" class="displayNone navigatorOverlay">
<div id="overlayLoading_SUBJAREA" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_3">
<div class="floatL">
Subject Area
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('SUBJAREA');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_SUBJAREA">
<ul class="refineResults floatL overlayUL" id="overlayul_SUBJAREA1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SUBJAREA2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SUBJAREA3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SUBJAREA4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_SUBJAREA" class="displayNone"><li></li></ul>
<div id="overlayFooter_SUBJAREA" class="displayNone">
<div class="floatR txtSmaller marginR8">
Sort on:
<select name="sclsb" onchange="handleClusterSorting('resultslist','b','SUBJAREA','selectedSubjectClusterCategories')" id="clusterSort_sclsb"><option selected="selected" value="# of results"># of results</option>
<option value="Alphabet">Alphabet</option></select>
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','SUBJAREA','selectedSubjectClusterCategories','11');" title="View more" id="vmore_SUBJAREA">
View more</a>
<span id="divider_SUBJAREA">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('SUBJAREA');" title="View fewer" id="vfew_SUBJAREA">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_4" class="dummyNav zoomFix" lang="cat_DOCTYPE">
<span id="checkArray_DOCTYPE" class="displayNone"></span>
<div id="heading_DOCTYPE" class="scopusClusterHeader ">
<div class="dragDropBox moveCursor">
Document Type </div>
<div id="collapse_DOCTYPE" class="clickBox">
<span class="btn_collapse" title="Click to close" onclick="collapseSection('DOCTYPE','collapse')">&nbsp;</span>
</div>
<span id="checkCount_DOCTYPE" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody " id="body_DOCTYPE">
<div id="viewMoreCount_DOCTYPE" class="displayNone">5</div>
<div id="viewLessCount_DOCTYPE" class="displayNone">0</div>
<div id="totalClusterCount_DOCTYPE" class="displayNone">6</div>
<ul class="refineResults txtSmaller" id="cluster_DOCTYPE">
    					
<li>
<div class="floatL">
<input name="selectedDocTypeClusterCategories" value="cp" id="cat_cp" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_cp">
Conference Paper
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(856)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedDocTypeClusterCategories" type="hidden">
<input value="cp" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedDocTypeClusterCategories" value="ar" id="cat_ar" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_ar">
Article
</label>
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Electric network analysis
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(256)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Electric network analysis" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_EXACTKEYWORD">
<li>
<div class="floatL">
<input name="selectedKeywordClusterCategories" value="Research" id="cat_Research" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Research">
Research
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(117)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Research" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedKeywordClusterCategories" value="Information systems" id="cat_Informationsystems" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Informationsystems">
Information systems
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(109)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Information systems" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedKeywordClusterCategories" value="Data mining" id="cat_Datamining" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Datamining">
Data mining
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(107)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Data mining" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedKeywordClusterCategories" value="Knowledge management" id="cat_Knowledgemanagement" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Knowledgemanagement">
Knowledge management
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(101)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Knowledge management" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedKeywordClusterCategories" value="Social sciences computing" id="cat_Socialsciencescomputing" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Socialsciencescomputing">
Social sciences computing
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(99)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedKeywordClusterCategories" type="hidden">
<input value="Social sciences computing" type="hidden">
</span>
	      			
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsKeyCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','EXACTKEYWORD','selectedKeywordClusterCategories','11');" title="View more" id="viewMoreLink_EXACTKEYWORD">
View more</a>
<span id="viewDivider_EXACTKEYWORD" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('EXACTKEYWORD');" title="View fewer" id="viewFewerLink_EXACTKEYWORD" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_EXACTKEYWORD" class="displayNone navigatorOverlay">
<div id="overlayLoading_EXACTKEYWORD" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_6">
<div class="floatL">
Keyword         
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('EXACTKEYWORD');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_EXACTKEYWORD">
<ul class="refineResults floatL overlayUL" id="overlayul_EXACTKEYWORD1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_EXACTKEYWORD2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_EXACTKEYWORD3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_EXACTKEYWORD4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_EXACTKEYWORD" class="displayNone"><li></li></ul>
<div id="overlayFooter_EXACTKEYWORD" class="displayNone">
<div class="floatR txtSmaller marginR8">
Sort on:
<select name="sclk" onchange="handleClusterSorting('resultslist','b','EXACTKEYWORD','selectedKeywordClusterCategories')" id="clusterSort_sclk"><option selected="selected" value="# of results"># of results</option>
<option value="A">A</option>
<option value="B">B</option>
<option value="C">C</option>
<option value="D">D</option>
<option value="E">E</option>
<option value="F">F</option>
<option value="G">G</option>
<option value="H">H</option>
<option value="I">I</option>
<option value="J">J</option>
<option value="K">K</option>
<option value="L">L</option>
<option value="M">M</option>
<option value="N">N</option>
<option value="O">O</option>
<option value="P">P</option>
<option value="Q">Q</option>
<option value="R">R</option>
<option value="S">S</option>
<option value="T">T</option>
<option value="U">U</option>
<option value="V">V</option>
<option value="W">W</option>
<option value="X">X</option>
<option value="Y">Y</option>
<option value="Z">Z</option>
<option value="0-9">0-9</option>
<option value="Other">Other</option></select>
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','EXACTKEYWORD','selectedKeywordClusterCategories','11');" title="View more" id="vmore_EXACTKEYWORD">
View more</a>
<span id="divider_EXACTKEYWORD">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('EXACTKEYWORD');" title="View fewer" id="vfew_EXACTKEYWORD">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_7" class="dummyNav zoomFix" lang="cat_AFFIL">
<span id="checkArray_AFFIL" class="displayNone"></span>
<div id="heading_AFFIL" class="scopusClusterHeader sideBarBorderBottom">
<div class="dragDropBox moveCursor">
Affiliation     </div>
<div id="collapse_AFFIL" class="clickBox">
<span class="btn_expand" title="Click to open" onclick="expandSection('AFFIL','open')">&nbsp;</span>	
</div>
<span id="checkCount_AFFIL" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody displayNone" id="body_AFFIL">
<div id="viewMoreCount_AFFIL" class="displayNone">5</div>
<div id="viewLessCount_AFFIL" class="displayNone">0</div>
<div id="totalClusterCount_AFFIL" class="displayNone">11</div>
<ul class="refineResults txtSmaller" id="cluster_AFFIL">
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60016930" id="cat_60016930" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60016930">
Beijing University of Posts and Telecommunications
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(22)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60016930" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60003892" id="cat_60003892" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60003892">
Arizona State University
</label>
										
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(16)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60003892" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60014662" id="cat_60014662" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60014662">
Drexel University
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(16)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60014662" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60025278" id="cat_60025278" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60025278">
Tsinghua University
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(16)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60025278" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60027950" id="cat_60027950" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60027950">
Carnegie Mellon University
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(15)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60027950" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_AFFIL">
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60010065" id="cat_60010065" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60010065">
University of Arizona
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(14)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60010065" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60005429" id="cat_60005429" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60005429">
National Taiwan University
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(12)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60005429" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60019499" id="cat_60019499" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60019499">
Chinese Academy of Sciences
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(12)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60019499" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60011048" id="cat_60011048" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60011048">
IBM Research
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(11)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60011048" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedAffiliationClusterCategories" value="60017366" id="cat_60017366" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_60017366">
IBM Thomas J. Watson Research Center
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(11)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedAffiliationClusterCategories" type="hidden">
<input value="60017366" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsAffilCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','AFFIL','selectedAffiliationClusterCategories','11');" title="View more" id="viewMoreLink_AFFIL">
View more</a>
<span id="viewDivider_AFFIL" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('AFFIL');" title="View fewer" id="viewFewerLink_AFFIL" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_AFFIL" class="displayNone navigatorOverlay">
<div id="overlayLoading_AFFIL" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_7">
<div class="floatL">
Affiliation     
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('AFFIL');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_AFFIL">
<ul class="refineResults floatL overlayUL" id="overlayul_AFFIL1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AFFIL2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AFFIL3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_AFFIL4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_AFFIL" class="displayNone"><li></li></ul>
<div id="overlayFooter_AFFIL" class="displayNone">
<div class="floatR txtSmaller marginR8">
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','AFFIL','selectedAffiliationClusterCategories','11');" title="View more" id="vmore_AFFIL">
View more</a>
<span id="divider_AFFIL">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('AFFIL');" title="View fewer" id="vfew_AFFIL">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_8" class="dummyNav zoomFix" lang="cat_COUNTRY_NAME">
<span id="checkArray_COUNTRY_NAME" class="displayNone"></span>
<div id="heading_COUNTRY_NAME" class="scopusClusterHeader sideBarBorderBottom">
<div class="dragDropBox moveCursor">
Country         </div>
<div id="collapse_COUNTRY_NAME" class="clickBox">
<span class="btn_expand" title="Click to open" onclick="expandSection('COUNTRY_NAME','open')">&nbsp;</span>	
</div>
<span id="checkCount_COUNTRY_NAME" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody displayNone" id="body_COUNTRY_NAME">
<div id="viewMoreCount_COUNTRY_NAME" class="displayNone">5</div>
<div id="viewLessCount_COUNTRY_NAME" class="displayNone">0</div>
<div id="totalClusterCount_COUNTRY_NAME" class="displayNone">11</div>
<ul class="refineResults txtSmaller" id="cluster_COUNTRY_NAME">
    	  					
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="United States" id="cat_UnitedStates" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_UnitedStates">
United States
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(364)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="United States" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="China" id="cat_China" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_China">
China
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(188)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="China" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="United Kingdom" id="cat_UnitedKingdom" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_UnitedKingdom">
United Kingdom
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(94)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="United Kingdom" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="Germany" id="cat_Germany" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Germany">
Germany
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(86)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="Germany" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="Taiwan" id="cat_Taiwan" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Taiwan">
Taiwan
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(76)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="Taiwan" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_COUNTRY_NAME">
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="Canada" id="cat_Canada" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Canada">
Canada
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(61)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="Canada" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="Australia" id="cat_Australia" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Australia">
Australia
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(56)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="Australia" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="South Korea" id="cat_SouthKorea" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_SouthKorea">
South Korea
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(51)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="South Korea" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="France" id="cat_France" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_France">
France
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(41)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="France" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedCountryClusterCategories" value="Spain" id="cat_Spain" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Spain">
Spain
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(33)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedCountryClusterCategories" type="hidden">
<input value="Spain" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsDocCntryCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','COUNTRY_NAME','selectedCountryClusterCategories','11');" title="View more" id="viewMoreLink_COUNTRY_NAME">
View more</a>
<span id="viewDivider_COUNTRY_NAME" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('COUNTRY_NAME');" title="View fewer" id="viewFewerLink_COUNTRY_NAME" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_COUNTRY_NAME" class="displayNone navigatorOverlay">
<div id="overlayLoading_COUNTRY_NAME" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_8">
<div class="floatL">
Country         
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('COUNTRY_NAME');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_COUNTRY_NAME">
<ul class="refineResults floatL overlayUL" id="overlayul_COUNTRY_NAME1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_COUNTRY_NAME2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_COUNTRY_NAME3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_COUNTRY_NAME4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_COUNTRY_NAME" class="displayNone"><li></li></ul>
<div id="overlayFooter_COUNTRY_NAME" class="displayNone">
<div class="floatR txtSmaller marginR8">
Sort on:
<select name="sclc" onchange="handleClusterSorting('resultslist','b','COUNTRY_NAME','selectedCountryClusterCategories')" id="clusterSort_sclc"><option selected="selected" value="# of results"># of results</option>
<option value="A">A</option>
<option value="B">B</option>
<option value="C">C</option>
<option value="D">D</option>
<option value="E">E</option>
<option value="F">F</option>
<option value="G">G</option>
<option value="H">H</option>
<option value="I">I</option>
<option value="J">J</option>
<option value="K">K</option>
<option value="L">L</option>
<option value="M">M</option>
<option value="N">N</option>
<option value="O">O</option>
<option value="P">P</option>
<option value="Q">Q</option>
<option value="R">R</option>
<option value="S">S</option>
<option value="T">T</option>
<option value="U">U</option>
<option value="V">V</option>
<option value="W">W</option>
<option value="X">X</option>
<option value="Y">Y</option>
<option value="Z">Z</option>
<option value="Undefined">Undefined</option></select>
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','COUNTRY_NAME','selectedCountryClusterCategories','11');" title="View more" id="vmore_COUNTRY_NAME">
View more</a>
<span id="divider_COUNTRY_NAME">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('COUNTRY_NAME');" title="View fewer" id="vfew_COUNTRY_NAME">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_9" class="dummyNav zoomFix" lang="cat_SCOPUSSRCTYPE">
<span id="checkArray_SCOPUSSRCTYPE" class="displayNone"></span>
<div id="heading_SCOPUSSRCTYPE" class="scopusClusterHeader sideBarBorderBottom">
<div class="dragDropBox moveCursor">
Source Type     </div>
<div id="collapse_SCOPUSSRCTYPE" class="clickBox">
<span class="btn_expand" title="Click to open" onclick="expandSection('SCOPUSSRCTYPE','open')">&nbsp;</span>	
</div>
<span id="checkCount_SCOPUSSRCTYPE" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody displayNone" id="body_SCOPUSSRCTYPE">
<div id="viewMoreCount_SCOPUSSRCTYPE" class="displayNone">5</div>
<div id="viewLessCount_SCOPUSSRCTYPE" class="displayNone">0</div>
<div id="totalClusterCount_SCOPUSSRCTYPE" class="displayNone">4</div>
<ul class="refineResults txtSmaller" id="cluster_SCOPUSSRCTYPE">
<li>
<div class="floatL">
<input name="selectedSourceTypeClusterCategories" value="p" id="cat_p" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_p">
Conference Proceedings
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(758)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSourceTypeClusterCategories" type="hidden">
<input value="p" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSourceTypeClusterCategories" value="j" id="cat_j" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_j">
Journals
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(350)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSourceTypeClusterCategories" type="hidden">
<input value="j" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSourceTypeClusterCategories" value="k" id="cat_k" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_k">
Book Series
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(132)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSourceTypeClusterCategories" type="hidden">
<input value="k" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedSourceTypeClusterCategories" value="d" id="cat_d" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_d">
Trade Publications
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(2)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedSourceTypeClusterCategories" type="hidden">
<input value="d" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsSrctypeCount" value="4" type="hidden">
							
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewFewerClusters('SCOPUSSRCTYPE');" title="View fewer" id="viewFewerLink_SCOPUSSRCTYPE" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_SCOPUSSRCTYPE" class="displayNone navigatorOverlay">
<div id="overlayLoading_SCOPUSSRCTYPE" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_9">
<div class="floatL">
Source Type     
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('SCOPUSSRCTYPE');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_SCOPUSSRCTYPE">
<ul class="refineResults floatL overlayUL" id="overlayul_SCOPUSSRCTYPE1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SCOPUSSRCTYPE2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SCOPUSSRCTYPE3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_SCOPUSSRCTYPE4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_SCOPUSSRCTYPE" class="displayNone"><li></li></ul>
<div id="overlayFooter_SCOPUSSRCTYPE" class="displayNone">
<div class="floatR txtSmaller marginR8">
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','SCOPUSSRCTYPE','selectedSourceTypeClusterCategories','4');" title="View more" id="vmore_SCOPUSSRCTYPE">
View more</a>
<span id="divider_SCOPUSSRCTYPE">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('SCOPUSSRCTYPE');" title="View fewer" id="vfew_SCOPUSSRCTYPE">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
<div id="navigator_10" class="dummyNav zoomFix" lang="cat_LANGUAGE">
<span id="checkArray_LANGUAGE" class="displayNone"></span>
<div id="heading_LANGUAGE" class="scopusClusterHeader sideBarBorderBottom">
<div class="dragDropBox moveCursor">
Language</div>
<div id="collapse_LANGUAGE" class="clickBox">
<span class="btn_expand" title="Click to open" onclick="expandSection('LANGUAGE','open')">&nbsp;</span>	
</div>
<span id="checkCount_LANGUAGE" class="displayNone selectedText"></span>
</div>
<div class="body dummyBody displayNone" id="body_LANGUAGE">
<div id="viewMoreCount_LANGUAGE" class="displayNone">5</div>
<div id="viewLessCount_LANGUAGE" class="displayNone">0</div>
<div id="totalClusterCount_LANGUAGE" class="displayNone">6</div>
<ul class="refineResults txtSmaller" id="cluster_LANGUAGE">
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="English" id="cat_English" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_English">
English
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(1,220)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="English" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="Chinese" id="cat_Chinese" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Chinese">
Chinese
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(13)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="Chinese" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="French" id="cat_French" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_French">
French
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(10)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="French" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
 		
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="German" id="cat_German" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_German">
German
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(1)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="German" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="Portuguese" id="cat_Portuguese" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Portuguese">
Portuguese
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(1)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="Portuguese" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul><ul class="displayNone refineResults txtSmaller" id="hidden_LANGUAGE">
<li>
<div class="floatL">
<input name="selectedLanguageClusterCategories" value="Spanish" id="cat_Spanish" class="overlaycloseCheck" type="checkbox">
</div>
<div class="floatL textCol">
<label class="floatL leftCol" for="cat_Spanish">
Spanish
</label>
<span style="background: none repeat scroll 0% 0% rgb(255, 255, 255);" class="floatR pointer cib_Span" title="Show preview">
<span class="floatL">(1)</span>
<span class="greyArrow floatL marginL2">&nbsp;</span>
<input value="selectedLanguageClusterCategories" type="hidden">
<input value="Spanish" type="hidden">
</span>
<span class="clearB"></span>
</div>
<div class="displayNone">&nbsp;</div>
<div class="clear"></div>
</li>
</ul>
<input name="clsLangCount" value="5" type="hidden">
<ul class="refineResultsViewLink txtSmaller">
<li>
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','LANGUAGE','selectedLanguageClusterCategories','6');" title="View more" id="viewMoreLink_LANGUAGE">
View more</a>
<span id="viewDivider_LANGUAGE" style="display:none;">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('LANGUAGE');" title="View fewer" id="viewFewerLink_LANGUAGE" style="display:none;">
View fewer</a>
</li>
</ul>
</div>
<div id="navigatorOverlay_LANGUAGE" class="displayNone navigatorOverlay">
<div id="overlayLoading_LANGUAGE" class="overlayLoading">
<img src="Scopus%20-%20Document%20search%20results%20Page%206_arquivos/loading_3.gif" alt="Loading" title="Loading" class="imageLoading">
</div>
<div class="headings" id="overlayHeading_10">
<div class="floatL">
Language
</div>
<div class="floatR">
<span class="btn_collapse_Cluster" title="Click to close" onclick="overlayHide('LANGUAGE');">&nbsp;</span></div>
<div class="clear"></div>
</div>
<div class="body txtSmaller" id="overlayBody_LANGUAGE">
<ul class="refineResults floatL overlayUL" id="overlayul_LANGUAGE1"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_LANGUAGE2"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_LANGUAGE3"><li></li></ul>
<ul class="refineResults floatL overlayUL" id="overlayul_LANGUAGE4"><li></li></ul>
<div class="clear"></div>
</div>
<ul id="overlayul_LANGUAGE" class="displayNone"><li></li></ul>
<div id="overlayFooter_LANGUAGE" class="displayNone">
<div class="floatR txtSmaller marginR8">
Sort on:
<select name="scll" onchange="handleClusterSorting('resultslist','b','LANGUAGE','selectedLanguageClusterCategories')" id="clusterSort_scll"><option selected="selected" value="# of results"># of results</option>
<option value="A">A</option>
<option value="B">B</option>
<option value="C">C</option>
<option value="D">D</option>
<option value="E">E</option>
<option value="F">F</option>
<option value="G">G</option>
<option value="H">H</option>
<option value="I">I</option>
<option value="J">J</option>
<option value="K">K</option>
<option value="L">L</option>
<option value="M">M</option>
<option value="N">N</option>
<option value="O">O</option>
<option value="P">P</option>
<option value="Q">Q</option>
<option value="R">R</option>
<option value="S">S</option>
<option value="T">T</option>
<option value="U">U</option>
<option value="V">V</option>
<option value="W">W</option>
<option value="X">X</option>
<option value="Y">Y</option>
<option value="Z">Z</option></select>
</div>
<div class="floatL txtSmaller marginL10 marginT5 marginT5">
<a class="jsLink" href="javascript:viewMoreClusters('resultslist','b','LANGUAGE','selectedLanguageClusterCategories','6');" title="View more" id="vmore_LANGUAGE">
View more</a>
<span id="divider_LANGUAGE">|</span>
<a class="jsLink" href="javascript:viewFewerClusters('LANGUAGE');" title="View fewer" id="vfew_LANGUAGE">
View fewer</a>
</div>
<div class="marginB5 alignTextCenter">
<input name="limitTo" value="Limit to" onclick="return ValidateClusters('limit to');" class="Bold" title="Limit to selected items" alt="Limit to selected items" type="submit">
<input name="exclude" value="Exclude" onclick="return ValidateClusters('exclude')" class="Bold marginL5" title="Exclude selected items" alt="Exclude selected items" type="submit">
</div>
<div class="clear"></div>
</div>
</div>
</div>
</div>
<div class="endrow"></div>
</div>
<script type="text/javascript" language="javascript" charset="utf-8">
var clusterState = "";
var sourcepage = "s";
showClusterStateInSession(clusterState);
</script>
<script type="text/javascript" language="javascript" charset="utf-8">
var requestedURL = window.location + "";
var loginURL = "/customer/authenticate/loginfull.url?targetURL="+escape(requestedURL)+"&cancelURL=targetURL";
var saveToSessionURL = "/standard/savetosession.url";
var saveToOpaqueURL = "/standard/savetoprofile.url";
var featureInaccessibleURL = "/personalization/featureInaccessible.url";
var activationRequiredURL = "/personalization/activationRequired.url?targetURL="+escape(requestedURL)+"&cancelURL=targetURL";
var saveClusterToOpaqueURL = "/standard/saveClusterToSession.url";
var currentClusterOrder = "PUBYEAR:AUTHOR_NAME_AND_ID:SUBJAREA:DOCTYPE:EXACTSRCTITLE:EXACTKEYWORD:AFFIL:COUNTRY_NAME:SCOPUSSRCTYPE:LANGUAGE" ;
var defaultClusterOrder = "PUBYEAR:AUTHOR_NAME_AND_ID:SUBJAREA:DOCTYPE:EXACTSRCTITLE:EXACTKEYWORD:AFFIL:COUNTRY_NAME:SCOPUSSRCTYPE:LANGUAGE" ;
var loadedCluserorder = currentClusterOrder;
var profileClusterOrder = "" ;
var sessionSortOrderKey = "clusterOrder" ;
var sessionSaveNavigatorsToProfileKey = "saveClusters" ;
var featureInaccessible = "false" ;	
var activationRequired = "false" ;
var currentWidgetOrder = "SearchWithin:RefineResults:MyAppToolBar"
var defaultWidgetOrder = "SearchWithin:RefineResults:MyAppToolBar" ;
var loadedWidgetOrder = currentWidgetOrder;
var profileWidgetOrder = "" ;
var sessionWidgetOrderKey = "widgetOrder";
if (currentClusterOrder.length==0){
Element.show('no_navigators');
}		
</script>
</div>
<div id="hr" class="hr"><hr></div>
<div id="clusterFooter" class="zoomFix">
<div id="NAVIGATOR_FOOTER" class="displayNone"></div>
<input name="displayClusteringCountFlag" value="f" type="hidden"> 
<script type="text/javascript">
var isShowSaveSettings = 'true';
</script>
<div class="bottom">  
<div class="bg3 paddingB7">
<div class="alignTextCenter paddingT5">
<input title="Limit to selected items" alt="Limit to selected items" class="Bold" onclick="return ValidateClusters('limit to');" value="Limit to" name="limitTo" type="submit">
<input title="Exclude selected items" alt="Exclude selected items" class="Bold marginL3" onclick="return ValidateClusters('exclude')" value="Exclude" name="exclude" type="submit">
</div>
<div class="exportRefine" title="Export all of the refine values to a CSV file">
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<a smt-title="Show author details" class="" href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602312912&amp;zone=" title="">Snášel, V.</a>, <a smt-title="Show author details" class="" href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36470249000&amp;zone=" title="">Horák, Z.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24479558600&amp;zone=" title="Show author details">Kočíbová, J.</a>, <a smt-title="Show author details" class="" href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7202760099&amp;zone=" title="">Abraham, A.</a>
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2009</div>
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<i>Proceedings - 2009 IEEE/WIC/ACM International Conference on Web 
Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 
Workshops 2009</i>
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<div id="previewAbstract1"><span class="txt">Since the availability of 
social networks data and the range of these data have significantly 
grown in recent years, new aspects have to be considered. In this paper 
we address computational complexity of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">networks</font> <font class="ScopusTermHighlight">analysis</font>
 and clarity of their visualization. Our approach uses combination of 
Formal Concept Analysis and well-known matrix factorization methods. The
 goal is to reduce the dimension of social network data and to measure 
the amount of information which is lost during the reduction. © 2009 
IEEE.</span></div>
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2009</div>
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<i>Conferences in Research and Practice in Information Technology Series</i>
101
, pp. 99-108
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0
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<div id="previewAbstract2"><span class="txt">Contemporary organisations 
incorporate large amount of invisible networks between their employees. 
The structure of such networks impacts the information fusion within the
 organisation. Taking into account the in uence of such network 
structures in predictive modeling will be beneficial for the quality of 
organisational strategic planning. Network mining methods (the <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 of large heterogeneous data sets) can extract information about the 
structure of such networks and the strategic positioning of each 
individual from various interaction data. We propose to integrate the 
output of network mining into the predictive modeling cycle in order to 
depict these influences. This paper demonstrates such approach by 
incorporating network centrality measures of actor closeness and actor 
betweeness in CART predictive modeling cycle. It presents a 
proof-of-concept application of this integrated approach to the case 
study of a contemporary university, which resembles some similarity with
 corporate organisations. The study utilises a data set about academic 
research activities collected over five years. The results of the study 
support the hypothesis that information about the network structures in a
 data set (whose impact is included through the centrality measures) can
 improve the accuracy of predictive analysis. © 2009, Australian 
Computer Society, Inc.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=12789613700&amp;zone=" title="Show author details">Gomez, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603787961&amp;zone=" title="Show author details">Pryke, S.</a>
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2009</div>
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<i>Association of Researchers in Construction Management, ARCOM 2009 - Proceedings of the 25th Annual Conference</i>
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<div id="previewAbstract3"><span class="txt">Project-based organisations
 are effective vehicles for knowledge transfer potentially benefiting 
all project actors. In the case of construction companies, operatives 
nourish their knowledge through experience across different 
organisations that are dedicated to the same activity, as well as 
involvement in technical training. Furthermore, members of a project 
group will determine how the culture of the project is perceived. The 
study sought to examine the network of principal cause-effect 
interactions between the members of a Colombian construction project 
focussing on the nature and characteristics of knowledge exchange 
between site operative. The research project dealt with interactions and
 socialisation activities and the way in which these activities 
supported the development of operative skills. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) was used to observe the communities of practice (COP) and their 
influence on operatives. Some networks function through the transmission
 of explicit knowledge to operatives that is later transformed into 
tacit knowledge (TK). Other networks provide working environments where 
TK is developed and practiced with other members. The SNA method 
demonstrates that COPs not only influence operatives, they also 
influence co-workers within the project and facilitate other, less 
central operative actors, to acquire TK.</span></div>
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2009</div>
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<i>ICIS 2009 Proceedings - Thirtieth International Conference on Information Systems</i>
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<div id="previewAbstract4"><span class="txt">Identifying community 
structure in networks is an important topic in data mining research. One
 of the challenges is to find local communities without requiring the 
global knowledge of the entire network. Exiting techniques have several 
limitations. First, there is no widely accepted definition for 
community. Second, these algorithms either lack good stopping criteria 
or depend on predefined threshold parameters. In this research I propose
 a local cohesion based algorithm to identify local communities in 
networks. This algorithm is grounded on the widely accepted group 
cohesion definition in <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 research. The algorithm is self-contained and does not depend on 
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The evaluation results show that the proposed algorithm is more 
effective than the benchmark algorithm and can identify meaningful local
 communities in very large networks such as the Amazon co-purchasing 
network.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23091573000&amp;zone=" title="Show author details">Kunegis, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16307497100&amp;zone=" title="Show author details">Lommatzsch, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602137102&amp;zone=" title="Show author details">Bauckhage, C.</a>
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2009</div>
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<i>WWW'09 - Proceedings of the 18th International World Wide Web Conference</i>
, pp. 741-750
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<div id="previewAbstract5"><span class="txt">We analyse the corpus of 
user relationships of the Slash-dot technology news site. The data was 
collected from the Slashdot Zoo feature where users of the website can 
tag other users as friends and foes, providing positive and negative 
endorsements. We adapt <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 techniques to the problem of negative edge weights. In particular, we 
consider signed variants of global network characteristics such as the 
clustering coefficient, node-level characteristics such as centrality 
and popularity measures, and link-level characteristics such as 
distances and similarity measures. We evaluate these measures on the 
task of identifying unpopular users, as well as on the task of 
predicting the sign of links and show that the network exhibits 
multiplicative transitivity which allows algebraic methods based on 
matrix multiplication to be used. We compare our methods to traditional 
methods which are only suitable for positively weighted edges. Copyright
 is held by the International World Wide Web Conference Committee 
(IW3C2).</span></div>
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2009</div>
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<i>Adaptive and Emergent Behaviour and Complex Systems - Proceedings of 
the 23rd Convention of the Society for the Study of Artificial 
Intelligence and Simulation of Behaviour, AISB 2009</i>
							
, pp. 46-51
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<div id="previewAbstract6"><span class="txt">Humans are autonomous, intelligent, and adaptive agents. By adopting <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 techniques, we submit a framework for the study of dynamic networks and
 demonstrate the use of actor-oriented specifications in longitudinal 
networks. Through the use of a unique command and control dataset from 
experiments run at the US Military Academy, we illustrate the power of 
testing hypotheses on actor utility profiles. We frame static, covariate
 factors onto communication networks, and find that statistical 
hypothesis testing indicates edge networks truly motivate soldiers to 
seek information, collaborate, and modify the social network around them
 into more comfortable configurations of triad closure and edge 
reciprocity, when compared to hierarchical networks: a finding with 
profound implications to the study of complex, adaptive social systems.</span></div>
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2009</div>
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<i>WMSCI 2009 - The 13th World Multi-Conference on Systemics, 
Cybernetics and Informatics, Jointly with the 15th International 
Conference on Information Systems Analysis and Synthesis, ISAS 2009 - 
Proc.</i>
1
, pp. 99-103
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<div id="previewAbstract7"><span class="txt">Many executives invest 
resources in restructuring their enterprises, drawing organizational 
charts to be dissatisfied with the results. They often missed the real 
functioning of the company because much of the work happens despite the 
formal structure of an organization. Employees form networks of 
relationships, allowing them to learn and have access to knowledge 
across divisions in order to accomplish their tasks. Mapping these 
organisational knowledge networks will help executives understanding how
 organizations perform, thus contributing to make a difference to 
business performance. This paper accomplishes the research on 
Organizational Knowledge Networks applied in an engineering company 
divided into five different divisions, distributed among six 
geographical points. The research was focused on the identification and 
analysis of knowledge and learning relationships among project managers 
from different divisions and offices in order to improve connectivity 
and break down the silos formed by divisions and offices to boost 
learning and knowledge flow processes among them. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 has been applied to map and visualize the patterns of relationships 
among project managers. Main results show poor relationship patterns 
among project managers working in different divisions and prove the 
smaller the division and office are the greater connectivity and 
relationships exist.</span></div>
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 capacités relationnelles des technologies de l'information: Le concept 
de capital technico-social a-t-il un sens? | [IT relational 
capabilities: Is the concept of technical-social capital meaningful?]</a>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55505882800&amp;zone=" title="Show author details">Fuhrer, C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55505868300&amp;zone=" title="Show author details">Cucchi, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55508876100&amp;zone=" title="Show author details">Picard, P.</a>
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2009</div>
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<i>14th International Conference of the Association Information and Management 2009, AIM 2009</i>
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<div id="previewAbstract8"><span class="txt">This article deals with the
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question: Is the concept of computer-based social capital meaningful? We
 pretend that the social capital influences the emergence of relational 
capacity for action. Moreover, information technology influences 
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data coming from <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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2009</div>
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<div id="previewAbstract9"><span class="txt">No organisation, no matter 
how large, can remain totally reliant on the stocks of new knowledge it 
generates itself. In order to keep abreast of the latest scientific and 
technological developments, R&amp;D organisations must continuously 
import knowledge from beyond the organisations boundaries. How does this
 external knowledge which is critical to success then become absorbed 
and integrated into the firm? Our paper addresses this question through 
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 (SNA) and interview evidence from a medical devices R&amp;D group, we 
find that the gatekeeper role is still vital, but no longer needs to be 
performed by a single individual. Instead, the modern R&amp;D group can 
keep abreast of the latest technological advances through a combination 
of Web-enabled internal and external communication specialists. A unique
 contribution this paper makes to the IT-enable social network 
literature is the development of an updated conceptual framework of how 
the gatekeeper role is performed in the modern R&amp;D group.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5322 LNAI
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<div id="previewAbstract10"><span class="txt">This research in progress 
paper reports on the results of a pilot study investigating the transfer
 of knowledge in a social network, such as a Community of Practice, that
 comprises members of various organisations and therefore represents 
knowledge transfer at an inter-organisational level. The study aims to 
identify and analyse knowledge transfer structures and processes in 
inter-organisational social networks, which are embedded in the larger 
R&amp;D network. This paper presents some interim results using a mixed 
method approach of case research and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 Specifically, initial relations between tie strength, type of knowledge
 transferred as well as preferred media characteristics were discovered.
 Most central organisations in the network were identified. From these 
findings, the overarching goal is to investigate where information and 
communication technology could be utilised for continuous <font class="ScopusTermHighlight">online</font> knowledge transfer. © 2009 Springer-Verlag.</span></div>
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<i>CORIA 2009: Actes de la Sixieme Conference Francophone en Recherche 
d'Information et Applications - Proceedings of the Sixth French 
Conference on Information Retrieval and Applications</i>
, pp. 351-362
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<div id="previewAbstract11"><span class="txt">While <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 often focuses on graph structure of social actors, an increasing number
 of communication networks now provide textual content within social 
activity (email, instant messaging, blogging, collaboration networks). 
We present an open source visualization software, GraphDuplex, which 
brings together social structure and textual content, adding a semantic 
dimension to social analysis. GraphDuplex eventually connects any number
 of social or semantic graphs together, and through dynamic queries 
enables user interaction and exploration across multiple graphs of 
different nature.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602844942&amp;zone=" title="Show author details">Montazemi, A.R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35754814900&amp;zone=" title="Show author details">Pittaway, J.J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6506739304&amp;zone=" title="Show author details">Keshavjee, K.</a>
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2009</div>
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<i>15th Americas Conference on Information Systems 2009, AMCIS 2009</i>
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, pp. 656-666
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<div id="previewAbstract12"><span class="txt">Healthcare reform has 
emphasized coordinated and integrated care - patient-centered care - for
 a decade. To that end, policymakers have invested in integration of 
healthcare providers' information flows. Research to date has studied 
healthcare actors' information needs but overlooked communicative 
exchanges among all participants in coordinating treatment plan 
decisions. Consequently, while medical literature asserts that patients 
should depend on information from healthcare providers to enable 
patients' participation in treatment plan decisions, the assertion has 
not been tested. To ameliorate this oversight, we conducted an empirical
 study of a patient-centered healthcare environment. Our study draws on 
dependency network diagramming (DND) and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) to elucidate the nature and structure of actors' communications 
in support of their information dependencies. The findings illustrate 
that although patients are well supported by personal communications 
with healthcare providers, they are disenfranchised from the integrated 
information technology within and between healthcare providers and its 
potential to support patients' participation in coordinated 
"patient-centered care" decisions. Furthermore, knowledge asymmetry 
between patients and healthcare providers should be considered in the 
selection and tailoring of healthcare information systems (IS).</span></div>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=55826&amp;origin=resultslist">International Conference on Information and Knowledge Management, Proceedings</a></i>
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<div id="previewAbstract13"><span class="txt">In the blog world, 
bloggers produce information, establish relationships with other 
bloggers in order to exchange information, and form a blog network, an <font class="ScopusTermHighlight">online</font>
 social network. In social network theory, information diffusion is said
 to occur through the relationships of the social network's 
constituents. Contrary to the social network theory, however, when the 
history of information diffusion that occurs in the actual blog world is
 examined, a majority of information spreads between the constituents 
without any established relationship. Moreover the phenomenon of 
explosive information diffusion is also observed. Using the real-world 
blog data, this paper reveals that these two phenomena are related to 
each other and examines the causes that induce explosive information 
diffusion. Copyright 2009 ACM.</span></div>
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2009</div>
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<i>WWW'09 - Proceedings of the 18th International World Wide Web Conference</i>
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<div id="previewAbstract14"><span class="txt">Social media websites 
promote diverse user interaction on media objects as well as user 
actions with respect to other users. The goal of this work is to 
discover community structure in rich media social networks, and observe 
how it evolves over time, through analysis of multi-relational data. The
 problem is important in the enterprise domain where extracting emergent
 community structure on enterprise social media, can help in forming new
 collaborative teams, aid in expertise discovery, and guide long term 
enterprise reorganization. Our approach consists of three main parts: 
(1) a relational hypergraph model for modeling various social context 
and interactions; (2) a novel hypergraph factorization method for 
community extraction on multi-relational social data; (3) an <font class="ScopusTermHighlight">online</font>
 method to handle temporal evolution through incremental hypergraph 
factorization. Extensive experiments on real-world enterprise data 
suggest that our technique is scalable and can extract meaningful 
communities. To evaluate the quality of our mining results, we use our 
method to predict users' future interests. Our prediction outperforms 
baseline methods (frequency counts, pLSA) by 36-250% on the average, 
indicating the utility of leveraging multi-relational social context by 
using our method. Copyright is held by the author/owner(s).</span></div>
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2009</div>
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<i>2009 International Conference on Web Information Systems and Mining, WISM 2009</i>
, art. no. 5368318
, pp. 32-38
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<div id="previewAbstract15"><span class="txt">Using comment information 
available from Digg we define a co-participation network between users. 
We focus on the analysis of this implicit network, and study the 
behavioral characteristics of users. Using an entropy measure, we infer 
that users at Digg are not highly focused and participate across a wide 
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after limiting our feature extraction to the first few hours of comment 
activity that follows a Digg submission. © 2009 IEEE.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55354754800&amp;zone=" title="Show author details">Lim, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36998751600&amp;zone=" title="Show author details">Malladi, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55452170100&amp;zone=" title="Show author details">Saldanha, T.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14060692200&amp;zone=" title="Show author details">Melville, N.P.</a>
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2009</div>
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<i>ICIS 2009 Proceedings - Thirtieth International Conference on Information Systems</i>
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<div id="previewAbstract16"><span class="txt">Though use of theory is 
critical in Information Systems (IS) research, the theoretical 
foundations of IS research have been understudied. Using <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>,
 we analyze theory usage in IS research published in MIS Quarterly and 
Information Systems Research from 1998 to 2006. We find Technology 
Acceptance Model, Resource-Based View and Game Theory to be the three 
most frequently used theories. While strong dominance is found in 
research focusing on Information Technology (IT) for individuals, 
organizations and markets, no theoretical dominance is found in IT for 
groups and IS development. Psychology, Economics and Sociology are 
disciplines IS researchers most frequently leverage for theories. 
Psychology contributes several theories representing a large fraction of
 the long tail of theories. Our analysis suggests that IS consists of a 
few distinctive clusters of research instead of a single core. Our 
results provide insights on theoretical foundations of IS and suggest 
research opportunities for scholars.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14058561100&amp;zone=" title="Show author details">Park, H.H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6505654518&amp;zone=" title="Show author details">Rethemeyer, R.K.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24824237200&amp;zone=" title="Show author details">Hatmaker, D.M.</a>
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2009</div>
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<i>Academy of Management 2009 Annual Meeting: Green Management Matters, AOM 2009</i>
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<div id="previewAbstract17"><span class="txt">What organizational 
factors explain connections between members of policy networks? Our 
previous work on policy networks and "network systems" suggests that 
resource dependence is a central factor in social structural 
arrangements. However, these efforts have not taken into account basic 
social network factors such as the tendency for networks to display 
reciprocity, transitive closure, prestige, or other common social 
network sub-structures. Our earlier work also relied on deterministic 
social network methods. In this article we use exponential random graph 
models (ERGM) - a stochastic technique for modeling social network data -
 to examine more closely the role network substructures and covariates 
such as influence, sector (public vs. private), diversity of funding 
sources, and so forth. The first section of this article discusses the 
policy network framework, resource dependence, and the need to control 
for network sub-structures. The second section reviews the case selected
 and research methods. In the third section we present findings from our
 longitudinal case study of an adult basic education policy network 
between 1998 ("Wave 1") and 2005 ("Wave 2") in a state we have 
pseudonymed "Newstatia." Using the theoretical framework from the first 
section and the case findings in section three, we weave together social
 capital and resource dependence to present the concept of "enacted 
interorganizational relationships." The last section concludes with a 
series of propositions regarding the nature and dynamics of ties in 
policy networks.</span></div>
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2009</div>
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<i>WWW'09 - Proceedings of the 18th International World Wide Web Conference</i>
, pp. 731-740
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<div id="previewAbstract18"><span class="txt">In this paper we give 
models and algorithms to describe and analyze the collaboration among 
authors of Wikipedia from a network analytical perspective. The edit 
network encodes who interacts how with whom when editing an article; it 
significantly extends previous network models that code author 
communities in Wikipedia. Several characteristics summarizing some 
aspects of the organization process and allowing the analyst to identify
 certain types of authors can be obtained from the edit network. 
Moreover, we propose several indicators characterizing the global 
network structure and methods to visualize edit networks. It is shown 
that the structural network indicators are correlated with quality 
labels of the associated Wikipedia articles. Copyright is held by the 
International World Wide Web Conference Committee (IW3C2).</span></div>
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2009</div>
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<i>Proceedings of the 3rd Workshop on Social Network Mining and Analysis, SNA-KDD '09</i>
, art. no. 1731013
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<div id="previewAbstract19"><span class="txt">This paper explores how 
information contained in the structure of the social graph can improve 
search result relevance on social networking websites. Traditional 
approaches to search include scoring documents for relevance based on a 
set of keywords or using the link structure across documents to infer 
quality and relevance. These approaches attempt to optimally match 
keywords to documents with little or no information about the searcher 
and no information about his network. This study analyzes 3.8M profile 
search queries from a large social networking site in conjunction with 
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search relevance methods, improves the ordering of profiles in search 
results. Copyright 2009 ACM.</span></div>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5621 LNCS
, pp. 364-373
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<div id="previewAbstract20"><span class="txt">User Innovation Networks 
(UIN) has been considered the open innovation model for this century as 
it functions entirely independently of manufacturers. This paper 
discusses two UIN cases, Daz3D, as well as Linux Dell and IBM 
cooperation as regards research challenges about the community of 
practice and interface used. It concludes that current technology only 
now started touching global and extreme collaboration for creativity and
 innovation. © 2009 Springer Berlin Heidelberg.</span></div>
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2009</div>
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<i>Computer Supported Collaborative Learning Practices, CSCL 2009 Community Events Proceedings - 9th International Conference</i>
2
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<div id="previewAbstract21"><span class="txt">Quantitative methods in 
educational research tend to be heavily reductionist and to disregard 
interaction; most statistical models include an assumption of no 
interaction. Qualitative methods allow complexity and interaction, but 
tend not to include representations or otherwise allow the reader to 
"see" the interaction as the researcher can. By combining traditional 
qualitative methods with statistical modeling, we are afforded a better 
opportunity to see aspects of a phenomenon, but not always greater 
integration; interpretation does not easily emerge from potentially 
divergent data sets. By including <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 which provides both summary statistics and graphical depiction of 
interaction we are afforded a better opportunity to examine 
collaborative work. Furthermore, technology facilitates collection and 
analysis of change over time in computer supported collaborative work. 
These methods enable a multifarious view of quantitative data, and allow
 for interpretation to more naturally emerge from multiple data sets. © 
ISLS.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=54891815100&amp;zone=" title="Show author details">Ho, Z.W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55057894200&amp;zone=" title="Show author details">Chang, K.T.-T.</a>
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<i>17th European Conference on Information Systems, ECIS 2009</i>
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<div id="previewAbstract22"><span class="txt">We argue that types of 
Simmelian-tied employee dyads (dyads embedded in three-person cliques) 
influences organizational justice perceptions, and knowledge sharing 
within and across organizational boundaries through virtual workgroups. 
We study the interaction between employees' advice and friendship ties, 
shared interpersonal, interactional, procedural and distributive justice
 perceptions, and the types of knowledge shared from a social network 
perspective. We predict that Simmelian-tied advice and friendship dyads 
influence justice perceptions, and in turn knowledge sharing. Compared 
to Simmelian-tied advice dyads, we suggest that Simmelian-tied 
friendship dyads were hypothesized to be strongly associated with 
congruent distributive, interpersonal, and interpersonal justice 
perceptions. Congruent procedural justice perceptions were likely to be 
associated with both Simmelian-tied advice and friendship ties. We 
hypothesized that distributive, procedural, and informational justice 
perceptions were likely to be shared across formal organizational 
boundaries through strong friendship ties. We also predicted that 
positive congruent procedural, interpersonal and informational justice 
perceptions influenced expert knowledge sharing while congruent 
distributive justice perceptions influenced product knowledge sharing.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55565209500&amp;zone=" title="Show author details">Ignacio, R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15061453100&amp;zone=" title="Show author details">Helms, R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15043525500&amp;zone=" title="Show author details">Brinkkemper, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55565316200&amp;zone=" title="Show author details">Zonneveld, A.</a>
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2009</div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 399-408
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<div id="previewAbstract23"><span class="txt">To identify possible 
deficiencies in knowledge sharing several authors proposed to apply a 
network perspective. In this perspective, the knowledge transfer 
relations between people are studied. The proposition in these 
researches is that the position of an individual in a network or the 
specific clustering of people into groups serves as an indicator 
concerning the efficiency or effectiveness of knowledge sharing. 
However, previous research learned that a network perspective might not 
reveal all deficiencies as it mainly focuses on the tacit dimension of 
knowledge. In this research, we seek to validate one of the network 
approaches to study the tacit dimension of knowledge sharing, which is 
called Knowledge Network Analysis. To validate the Knowledge Network 
Analysis technique we conducted a case study, at an international 
product software supplier. A knowledge network analysis was conducted 
and the outcome of this analysis is compared with a qualitative study 
based on interviews and direct observations that focused on the tacit as
 well as the explicit dimension of knowledge. To analyze the qualitative
 data we developed a new model called Knowledge Sharing Environment 
Model (KSEM), which is capable of identifying and quantifying knowledge 
sharing bottlenecks. A total of eight bottlenecks identified by KNA were
 analyzed by means of the KSEM. Hence, six out of eight bottlenecks were
 validated. This case study demonstrates that Knowledge Network Analysis
 is a good tool for the identification of bottlenecks. However, it was 
suggested to combine the Knowledge Network Analysis with another 
research method such as the KSEM to validate and study the causes behind
 the identified bottlenecks.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36172715600&amp;zone=" title="Show author details">Wang, G.A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36470257500&amp;zone=" title="Show author details">Jiao, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7401635358&amp;zone=" title="Show author details">Fan, W.</a>
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2009</div>
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<i>ICIS 2009 Proceedings - Thirtieth International Conference on Information Systems</i>
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<div id="previewAbstract24"><span class="txt">Knowledge-based 
communities are popular Web-based tools that allow members to share and 
seek knowledge globally. However, research on how to search effectively 
within such knowledge repositories is scant. In this paper we study the 
problem of finding authoritative documents for user queries within a 
knowledge-based community. Unlike prior research on the ranking function
 design which considers only content or hyperlink information, we 
leverage the social network information embedded in the rich social 
media, in addition to content, to design novel ranking strategies. Using
 the Knowledge Adoption Model as the guiding theoretical framework, we 
design features that gauge the two major factors affecting users' 
knowledge adoption decisions: argument quality (AQ) and source 
credibility (SC). We design two ranking strategies that blend these two 
sources of evidence with the content-based relevance judgment. A 
preliminary study using a real world knowledge-based community showed 
that both AQ and SC features improved search effectiveness.</span></div>
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1025
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<a href="http://www.scopus.com/record/display.url?eid=2-s2.0-84870266828&amp;origin=resultslist&amp;sort=plf-f&amp;src=s&amp;st1=%22social+network+analysis%22+AND+online&amp;nlo=&amp;nlr=&amp;nls=&amp;sid=F24707DC9D3767AFFD5F36FE052141BF.CnvicAmOODVwpVrjSeqQ%3a20&amp;sot=b&amp;sdt=b&amp;sl=51&amp;s=TITLE-ABS-KEY%28%22social+network+analysis%22+AND+online%29&amp;relpos=1024&amp;relpos=24&amp;searchTerm=TITLE-ABS-KEY%28%5C%26quot%3Bsocial+network+analysis%5C%26quot%3B+AND+online%29" onclick="javascript:submitRecord('2-s2.0-84870266828','24','0');">A study of MIS scholar community development via a collaboration network structures analysis</a>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55505752800&amp;zone=" title="Show author details">Chang, C.-H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8725971900&amp;zone=" title="Show author details">Wang, J.-C.</a>
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2009</div>
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<i>15th Americas Conference on Information Systems 2009, AMCIS 2009</i>
1
, pp. 683-700
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<div id="previewAbstract25"><span class="txt">The objective of this 
study is to apply collaborative networks to understanding the 
development process of the Management Information System (MIS) journals'
 knowledge community. This research explores four phenomena: whether a 
co-author network depends on star collaborators, whether this network is
 a small world, the structural cohesion within the co-author network, 
and central scholars. We found that the MIS community has a small-world 
structure and high structural cohesion, so the MIS network is a dense 
cluster. Another finding was that a small number of researchers receive 
disproportionate recognition in MIS communities, indicating the presence
 of preferential attachment. This means that the MIS network contains 
clear star authors. Furthermore, we infer how a structural network 
affects knowledge diffusion and information diffusion. In addition, this
 study discusses changes in each journal's central scholars to observe 
patterns of publication for each journal published by a private 
for-profit organization or sponsored by academic societies.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7003653192&amp;zone=" title="Show author details">Bodner, D.A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=12242136700&amp;zone=" title="Show author details">Mutnury, B.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7003304815&amp;zone=" title="Show author details">Cases, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7103131687&amp;zone=" title="Show author details">Rouse, W.B.</a>
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2009</div>
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<i>Designcon 2009</i>
3
, pp. 1599-1614
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<div id="previewAbstract26"><span class="txt">Recent attention has 
focused on productivity and value creation in the service sector through
 the advent of service science, management and engineering. Quantitative
 methods increasingly are being applied to the study of service systems 
to improve the design, planning and control of service delivery. 
Designing electronic products can be viewed as a service system, in 
which a design team or teams provide services that lead eventually to a 
product specification and/or design. This paper discusses how 
discrete-event simulation and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 can be used to study and improve design processes and service delivery,
 and it presents a case study involving design of computer servers.</span></div>
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2009</div>
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<i>Proceedings of the 8th IASTED International Conference on Web-based Education, WBE 2009</i>
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<div id="previewAbstract27"><span class="txt">The proceedings contain 62
 papers. The topics discussed include: standards in distance learning; a
 training path advisor for lifelong learning; constructing a 
personalized learning system for an <font class="ScopusTermHighlight">online</font>
 3D virtual museum; transformation of a physical experiment into a 
virtual experiment for web applications; learning design usage example 
for holistic e-learning; multi-cultural educational group work in 3D 
collaborative virtual environments: identifying challenges; building a 
quality web based environment starting from a testing and assessment 
infrastructure; mapping e-learning interactions using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>;
 web-based teacher education program for acquiring the theory and method
 of cooperative learning; the effect on collaborative mathematics 
centered distance joint class at elementary schools; and learning 
science through a web-based virtual reality courseware: an evaluation of
 students' outcomes of learning.</span></div>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5794 LNCS
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<div id="previewAbstract28"><span class="txt">Current Learning Management Systems generically provide <font class="ScopusTermHighlight">online</font>
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<i>Proceedings of the International Conference on Information Technology Interfaces, ITI</i>
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<div id="previewAbstract29"><span class="txt">In the past few years researchers have started examining macro structural properties of friendship and messaging relations in <font class="ScopusTermHighlight">online</font>
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important question: what micro processes create that structure? In this 
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5794 LNCS
, pp. 181-195
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<div id="previewAbstract30"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 facilitation in a cross-cultural collaborative learning context is 
increasingly prevalent, but limited research has been conducted on the 
related issues, especially on facilitation via weblogs, which are 
increasingly used as an educational tool and becoming a significant 
component of many web-based learning environments. In this paper we 
address two issues: (i) how facilitators use weblogs as an educational 
instrument to support the students' activities in a fully <font class="ScopusTermHighlight">online</font>
 multi-national collaborative learning course; (ii) whether facilitation
 style plays a role in influencing the learners' working styles and 
performance in a setting where weblogs have been heavily used. The 
analysis results indicate the practicality of deploying weblogs as an 
effective <font class="ScopusTermHighlight">online</font> facilitation 
and learning tool, the rather intricate relationships between 
facilitation and learning styles mediated by some socio-cultural 
factors, and the usefulness of our proposed weblog analysis scheme. © 
2009 Springer Berlin Heidelberg.</span></div>
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<i>Proceedings of the ACM SIGKDD Workshop on CyberSecurity and Intelligence Informatics, CSI-KDD in Conjunction with SIGKDD'09</i>
, art. no. 1599284
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<div id="previewAbstract31"><span class="txt">Intelligence and law 
enforcement force make use of terrorist and criminal social networks to 
support their investigations such as identifying suspects, terrorist or 
criminal subgroups, and their communication patterns. Social networks 
are valuable resources but it is not easy to obtain information to 
create a complete terrorist or criminal social network. Missing 
information in a terrorist or criminal social network always diminish 
the effectiveness of investigation. An individual agency only has a 
partial terrorist or criminal social network due to their limited 
information sources. Sharing and integration of social networks between 
different agencies increase the effectiveness of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 Unfortunately, information sharing is usually forbidden due to the 
concern of privacy preservation. In this paper, we introduce the KNN 
algorithm for subgraph generation and a mechanism to integrate the 
generalized information to conduct <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 Generalized information such as lengths of the shortest paths, number 
of nodes on the boundary, and the total number of nodes is constructed 
for each generalized subgraphs. By utilizing the generalized information
 shared from other sources, an estimation of distance between nodes is 
developed to compute closeness centrality. Two experiments have been 
conducted with random graphs and the Global Salafi Jihad terrorist 
social network. The result shows that the proposed technique improves 
the accuracy of closeness centrality measures substantially while 
protecting the sensitive data. Copyright 2009 ACM.</span></div>
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<i>2009 International Conference on Education Technology and Computer, ICETC 2009</i>
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<div id="previewAbstract32"><span class="txt">The proceedings contain 73
 papers. The topics discussed include: the transformative promise of 
ICTs for the education of architects in Taiwan; experimental evaluation 
of SZ-2 phase coding to mitigate range ambiguity; analytic scoring of 
landscape CAD course based on BP neural network; a novel Gui simulation 
program designed for teaching of underground power cables; students' 
interactions in <font class="ScopusTermHighlight">online</font> asynchronous discussion forum: a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>;
 variable speed drive of single phase induction motor using frequency 
control method; an FPGA based architecture of a novel reconfigurable 
radio processor for software defined radio; implementation of language 
interpreter based on reusable components; some principles for good 
practices of e-learning in continuing education institutions; and fuzzy 
PID sliding mode controller design for the position control of a DC 
motor.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25824924600&amp;zone=" title="Show author details">Erlin</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25825824000&amp;zone=" title="Show author details">Yusof, N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35609963600&amp;zone=" title="Show author details">Rahman, A.A.</a>
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<i>2009 International Conference on Education Technology and Computer, ICETC 2009</i>
, art. no. 5169446
, pp. 25-29
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<div id="previewAbstract33"><span class="txt">Existing learning 
management system (LMS) provide limited information regarding the 
communication structure of group, level of participation, identifying 
who is central actors and other structural characteristics of the 
discussion forum. The instructors of an <font class="ScopusTermHighlight">online</font>
 class are not provided with those structural indicators that would 
allow them to evaluate the participation and interaction among students 
in their classes. In many instances, only statistical information, such 
as frequency of postings is encompassed, but this is not a very useful 
measurement for the interaction activity. This paper discusses the 
analysis of students' interactions in an <font class="ScopusTermHighlight">online</font> asynchronous discussion forum (OADF) using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> (SNA) method. The visual objects that represent these <font class="ScopusTermHighlight">online</font> interactions are demonstrated and explained. The findings showed that <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 provide more meaningful students' interactions analysis in term of 
information of communication structures. This approach can be used by 
instructors to assess social interactions in terms of network structure 
parameters. © 2009 IEEE.</span></div>
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<i>2009 IEEE International Conference on Information Reuse and Integration, IRI 2009</i>
, art. no. 5211538
, pp. 126-131
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<div id="previewAbstract34"><span class="txt">Mashup allows users to integrate different kinds of sources together. The ProgrammableWeb.com is a popular <font class="ScopusTermHighlight">online</font>
 social mashup site that enables users to publish mashups. In this 
paper, we discover user behavior pattern in mashup community by studying
 the network and clustering properties of ProgrammableWeb.com. Moreover,
 we define a new concept - mashup entropy to evaluate the diversity of 
mashup community. The results prove that mashup community possesses 
scale-free property. The frequently used APIs and annotated tags attract
 large amounts of users. People who have similar ideas tend to have 
similar behavior. Finally, we find that the overall mashup entropy 
decreases as time goes by, which means that users tend to reuse several 
design patterns in creating mashups. ©2009 IEEE.</span></div>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=101510&amp;origin=resultslist">Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining</a></i>
, pp. 527-535
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<div id="previewAbstract35"><span class="txt">This paper aims at 
discovering community structure in rich media social networks, through 
analysis of time-varying, multi-relational data. Community structure 
represents the latent social context of user actions. It has important 
applications in information tasks such as search and recommendation. 
Social media has several unique challenges. (a) In social media, the 
context of user actions is constantly changing and co-evolving; hence 
the social context contains time-evolving multi-dimensional relations. 
(b) The social context is determined by the available system features 
and is unique in each social media website. In this paper we propose 
MetaFac (MetaGraph Factorization), a framework that extracts community 
structures from various social contexts and interactions. Our work has 
three key contributions: (1) metagraph, a novel relational hypergraph 
representation for modeling multi-relational and multi-dimensional 
social data; (2) an efficient factorization method for community 
extraction on a given metagraph; (3) an on-line method to handle 
time-varying relations through incremental metagraph factorization. 
Extensive experiments on real-world social data collected from the Digg 
social media website suggest that our technique is scalable and is able 
to extract meaningful communities based on the social media contexts. We
 illustrate the usefulness of our framework through prediction tasks. We
 outperform baseline methods (including aspect model and tensor 
analysis) by an order of magnitude. Copyright 2009 ACM.</span></div>
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2009</div>
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<div id="previewAbstract36"><span class="txt">Social network services 
such as Facebook provide new data for social science research into, for 
example, the role of individual characteristics in friendship formation 
and the diffusion of tastes in social networks. This article assesses 
the potential of social network services for social science research in 
two ways. First, it is argued that social scientists conduct hyperlink 
analysis differently to applied physicists and researchers from the 
library and information sciences, and face constraints (relating to 
theory, methods and availability of appropriate tools) that are not 
encountered in the other disciplinary approaches. However, the 
constraints regarding theory and methods are less likely to be faced by 
researchers of <font class="ScopusTermHighlight">online</font> social 
networks, and for this reason, the rise of Facebook and other similar 
services is a potential boon for empirical social scientists interested 
in networks. The second part of the article focuses specifically on the 
availability of research tools, and it is argued that social network 
services may eventually serve as e-Research platforms for delivering <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> tools. © 2009 SAGE Publications.</span></div>
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<div id="previewAbstract37"><span class="txt">Large volumes of <font class="ScopusTermHighlight">online</font>
 business news provide an opportunity to explore various aspects of 
companies. A news story pertaining to a company often cites other 
companies. Using such company citations we construct an intercompany 
network, employ <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 techniques to identify a set of attributes from the network structure, 
and feed the attributes to machine learning methods to predict the 
company revenue relation (CRR) that is based on two companies' relative 
quantitative financial data. Hence, we seek to understand the power of 
network structural attributes in predicting CRRs that are not described 
in the news or known at the time the news was published. The network 
attributes produce close to 80% precision, recall, and accuracy for all 
87,340 company pairs in the network. This approach is scalable and can 
be extended to private and foreign companies for which financial data is
 unavailable or hard to procure. © 2009 Elsevier B.V. All rights 
reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24480585100&amp;zone=" title="Show author details">Chen, B.-W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7701338706&amp;zone=" title="Show author details">Wang, J.-F.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7701339012&amp;zone=" title="Show author details">Wang, J.-C.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=56190&amp;origin=resultslist">Proceedings - IEEE International Symposium on Circuits and Systems</a></i>
, art. no. 5117854
, pp. 738-741
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<div id="previewAbstract38"><span class="txt">Exploration techniques of 
video knowledge have been proposed for years to help people discover the
 details about videos. However, existing systems still yield limited 
information for users. In this paper, we present a video knowledge 
browsing system, which can establish the framework of a video based on 
its summarized contents and expand them by using <font class="ScopusTermHighlight">online</font>
 correlated media. Thus, users can not only browse key points of a video
 efficiently but also focus on what they are interested in. In order to 
construct the fundamental system, we make use of our previous proposed 
approaches to transforming a video into a graph. After the relational 
graph is built up, the <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> is then performed to explore <font class="ScopusTermHighlight">online</font>
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enhance the results of the network analysis. The experiments demonstrate
 that our system can achieve better performance than the traditional 
systems. ©2009 IEEE.</span></div>
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<i>2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009</i>
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<div id="previewAbstract40"><span class="txt">The proceedings contain 78
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network perspective within a Spanish knowledge intensive company; a 
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<div id="previewAbstract41"><span class="txt">The increased <font class="ScopusTermHighlight">online</font>
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<div id="previewAbstract42"><span class="txt"><font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">analysis</font>
 focuses on patterns of relations between and among people, 
organizations, states, etc. It aims to describe networks of relations as
 fully as possible, identify prominent patterns in such networks, trace 
the flow of information through them, and discover what effects these 
relations and networks have on people and organizations. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> offers a very promising potential for analyzing human-human interactions in <font class="ScopusTermHighlight">online</font>
 communities (discussion boards, newsgroups, virtual organizations). 
This Tutorial provides an overview of this analytic technique and 
demonstrates how it can be used in Human Computer Interaction (HCI) 
research and practice, focusing especially on Computer Mediated 
Communication (CMC). This topic acquires particular importance these 
days, with the increasing popularity of social networking websites 
(e.g., youtube, myspace, MMORPGs etc.) and the research interest in 
studying them. © 2009 Springer Berlin Heidelberg.</span></div>
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<i>Proceedings - International Conference on Advanced Information Networking and Applications, AINA</i>
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<div id="previewAbstract43"><span class="txt">User Generated Content 
(UGC) plays a key role in the current and future e-commence at the era 
of Web 2.0. As an important form of UGC, the <font class="ScopusTermHighlight">online</font>
 auction site eBay has enjoyed tremendous growth rates since its 
inception. Many social networks emerge across different communities on 
eBay. The notion of viral marketing has been proposed in both literature
 and practice. However, in order to find the "opinion leader" in the 
social network, marketers need to have a sound analytic tool to rank 
potential buyers. In order to tackle this issue, this paper propose a 
BuyerRank, a <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
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review of recent work on SNA and viral marketing in the light of the Web
 2.0 e-commerce context. © 2009 IEEE.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5686 LNCS
, pp. 424-433
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<div id="previewAbstract44"><span class="txt"><font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> is one of effective methods and techniques to analyze the interactions in <font class="ScopusTermHighlight">online</font>
 collaborative learning. This paper introduces our researches in which a
 web-based system visualizing and analyzing interactions in <font class="ScopusTermHighlight">online</font>
 collaborative learning was developed. Firstly, the function model, user
 interface and ar0063hitecture of the system are presented. Then, Three 
key steps and technologies in the implementation of the system are 
described. Lastly, we presented the case study in which the system is 
used to analyze and visualize the structures of interaction network in 
the collaborative learning. The case study proved that the system can 
visualize the socio-gram of the interaction network in different view, 
and can calculate the structures' indexes of the interaction interwork. ©
 2009 Springer Berlin Heidelberg.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16302255800&amp;zone=" title="Show author details">Pfeil, U.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602402531&amp;zone=" title="Show author details">Zaphiris, P.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=19419&amp;origin=resultslist">Computers in Human Behavior</a></i>
25
(5)
, pp. 1139-1155
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<div id="previewAbstract45"><span class="txt">In this paper, we study the social network structure of an <font class="ScopusTermHighlight">online</font> discussion board within SeniorNet, an empathic <font class="ScopusTermHighlight">online</font> community for older people. We apply <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA) to analyse the communication patterns and relationships between 
members of the discussion board. In addition to looking at the structure
 of the exchanged messages within the discussion board as a whole, we 
also investigate associations between the communication content and the 
social network patterns. Our findings show distinct differences between 
the social network patterns of empathic and non-empathic communications.
 For example, members are more connected and closer to each other in the
 social networks that are based on empathic communication compared to 
non-empathic communication. Additionally our results show that the type 
of empathic communication (e.g. different kinds of support) is linked to
 the social network structure within the discussion board. © 2009 
Elsevier Ltd. All rights reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602476265&amp;zone=" title="Show author details">Toral, S.L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16316579300&amp;zone=" title="Show author details">Martínez-Torres, M.R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6701637771&amp;zone=" title="Show author details">Barrero, F.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35077024500&amp;zone=" title="Show author details">Cortés, F.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=17493&amp;origin=resultslist">Internet Research</a></i>
19
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, pp. 378-392
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<div id="previewAbstract46"><span class="txt">Purpose: A large variety of <font class="ScopusTermHighlight">online</font>
 communities have emerged during the last years as a result of the 
challenges faced by both the business and scientific worlds. This trend 
has also been promoted by the development of internet and new Web 2.0 
technologies. In this context, this paper is focused on the determinants
 of success of <font class="ScopusTermHighlight">online</font> communities. But, as a difference from other studies, these determinants are analyzed from the <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 perspective. Several constructs related to the community organization 
as a social network are proposed and their interrelations are 
hypothesized in a general research framework. The obtained results test 
the proposed model providing the most relevant antecedents of the 
project success. Design/methodology/approach: A case study based on 
Linux ports to non-conventional processor and environments is used to 
test the proposed model. Structural equation modeling analysis is used 
to validate the structural proposed model. Findings: The main 
antecedents of <font class="ScopusTermHighlight">online</font> 
communities' success, quantifying the strength of the relation through 
the standardized path coefficients. Research limitations/implications: 
The research is limited to a particular set of <font class="ScopusTermHighlight">online</font>
 communities engaged with the development of the non-conventional Linux 
ports. However, they constitute a representative set of communities in 
the field of the open source projects (OSS) development, which are 
typically developed using a community of support. Originality/value: 
This paper fulfils the main antecedents causing the successful 
development of Internet virtual communities. Instead of using sources of
 data coming from users' surveys, this study employs community 
interactions as a source of data. Results have important implications 
over the development of <font class="ScopusTermHighlight">online</font> 
communities, like software business models based on virtual communities 
and open source software. © Emerald Group Publishing Limited.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=27067784100&amp;zone=" title="Show author details">Nasir, A.N.M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24468984100&amp;zone=" title="Show author details">Selamat, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35614587200&amp;zone=" title="Show author details">Selamat, M.H.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5465 LNAI
, pp. 137-146
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<div id="previewAbstract47"><span class="txt">Currently, politic is one 
of the critical and hot issues in Malaysia. There are many aspects that 
are related with politics. These politic aspects are mainly about 
spreading rumors and information through cyberspace that created 
positive and negative effects to the political situations in Malaysia. 
There are many branches of cyberspace that can be used by the Internet 
users to channel their opinions such as websites, forums and blogs which
 contain the political issues in Malaysia. In this paper, we have 
analyzed an adaptive model of web mining using Artificial Immune System 
(AIS) to retrieve the list of URLs that have relevant information on 
political issues in Malaysia. In addition, we have also used a concept 
of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 in order to understand the relationships among the websites and web 
pages related to the political issues in Malaysia. The results from this
 model have been used to analyze the social networks and the impact of <font class="ScopusTermHighlight">online</font> community which contribute to the outcome of Malaysia's 12th general election. © Springer-Verlag Berlin Heidelberg 2009.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26658035400&amp;zone=" title="Show author details">Hamulic, I.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26657807800&amp;zone=" title="Show author details">Bijedic, N.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=17700156418&amp;origin=resultslist">Procedia - Social and Behavioral Sciences</a></i>
1
(1)
, pp. 2269-2273
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<div id="previewAbstract48"><span class="txt">FIT has a large virtual 
community, developed for DL students, but including the growing number 
of in-situ students. Through the last five years, most of the students 
have accepted and used FIT Community Server (FITCS) for interactions, 
but the extent of knowledge sharing was never measured. It was 
determined that FITCS is a small-world scale-free network, with several 
hubs: some administrators and some spammers. Now we determined 
characteristics of the social network, such as density, centrality, 
degree, closeness and betweenness, for overall communication in first 
two semesters and for two subjects in order to estimate knowledge 
sharing. © 2009.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=10043514200&amp;zone=" title="Show author details">Park, H.W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8891686200&amp;zone=" title="Show author details">Kluver, R.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=14735&amp;origin=resultslist">Government Information Quarterly</a></i>
26
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<div id="previewAbstract49"><span class="txt">In recent years, as 
information technologies have grown in sophistication and become more 
fully integrated into daily lifestyles, a general expectation has arisen
 that the internet has the potential to reconfigure social and political
 relationships, and to create new political configurations. Blogging, in
 particular, has been seen to have significant potential to merge the 
public and the personal in new ways, potentially altering the nature of 
politics, particularly in nations where political processes are 
formalistic and highly regulated. As an example, politicians who blog 
have developed a new approach to communicating with their 
constituencies, in that the private thoughts of the political actor are 
expressed in a relatively unmediated environment. This study, which 
examines trends in blog linkages among Assembly members in Korea, 
provides a longitudinal analysis of blog linkages in order to assess the
 long term implications of new media technologies in Korean society and 
politics. The data were gathered from the blogs of Korea's National 
Assembly members for 2005 and 2006. An analysis of these links indicates
 that, indeed, there is an increased use of blogs among National 
Assembly members. However, it seems that over time, the network becomes 
sparser, less integrated, and more decentralized. This study also 
suggests that offline imperatives for political organization figure 
prominently in the motives of establishing <font class="ScopusTermHighlight">online</font> linkages to other political blogs. © 2009 Elsevier Inc. All rights reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603686592&amp;zone=" title="Show author details">Bollen, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602198600&amp;zone=" title="Show author details">Van de Sompel, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6701625591&amp;zone=" title="Show author details">Hagberg, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25321100500&amp;zone=" title="Show author details">Chute, R.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=10600153309&amp;origin=resultslist">PLoS ONE</a></i>
4
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, art. no. e6022
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<div id="previewAbstract50"><span class="txt">Background: The impact of 
scientific publications has traditionally been expressed in terms of 
citation counts. However, scientific activity has moved <font class="ScopusTermHighlight">online</font>
 over the past decade. To better capture scientific impact in the 
digital era, a variety of new impact measures has been proposed on the 
basis of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and usage log data. Here we investigate how these new measures relate 
to each other, and how accurately and completely they express scientific
 impact. Methodology: We performed a principal component analysis of the
 rankings produced by 39 existing and proposed measures of scholarly 
impact that were calculated on the basis of both citation and usage log 
data. Conclusions: Our results indicate that the notion of scientific 
impact is a multi-dimensional construct that can not be adequately 
measured by any single indicator, although some measures are more 
suitable than others. The commonly used citation Impact Factor is not 
positioned at the core of this construct, but at its periphery, and 
should thus be used with caution.</span></div>
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2009</div>
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<div id="previewAbstract51"><span class="txt">Electronic networks of 
practice are computer-mediated social spaces where individuals working 
on similar problems self-organize to help each other and share 
knowledge, advice, and perspectives about their occupational practice or
 common interests. These interactions occur through message postings to 
produce an on-line public good of knowledge, where all participants in 
the network can then access this knowledge, regardless of their active 
participation in the network. Using theories and concepts of collective 
action and public goods, five hypotheses are developed regarding the 
structural and social characteristics that support the <font class="ScopusTermHighlight">online</font> provision and maintenance of knowledge in an electronic network of practice. Using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 we examine the structure of message contributions that produce and 
sustain the public good. We then combine the results from network 
analysis with survey results to examine the underlying pattern of 
exchange, the role of the critical mass, the quality of the ties 
sustaining participation, the heterogeneity of resources and interests 
of participants, and changes in membership that impact the structural 
characteristics of the network. Our results suggest that the electronic 
network of practice chosen for this study is sustained through 
generalized exchange, is supported by a critical mass of active members,
 and that members develop strong ties with the community as a whole 
rather than develop interpersonal relationships. Knowledge contribution 
is significantly related to an individual's tenure in the occupation, 
expertise, availability of local resources and a desire to enhance one's
 reputation, and those in the critical mass are primarily responsible 
for creating and sustaining the public good of knowledge. Finally, we 
find that this structure of generalized exchange is stable over time 
although there is a high proportion of member churn in the network. © 
2009 Elsevier B.V. All rights reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23393813300&amp;zone=" title="Show author details">Potgieter, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26538441500&amp;zone=" title="Show author details">April, K.A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26538437500&amp;zone=" title="Show author details">Cooke, R.J.E.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25628228100&amp;zone=" title="Show author details">Osunmakinde, I.O.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=4700151612&amp;origin=resultslist">E:CO Emergence: Complexity and Organization</a></i>
11
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<div id="previewAbstract52"><span class="txt">This article describes 
research into the discovery and modelling of emergent temporal phenomena
 in social networks. It summarizes experimental results that bring 
together two views in contemporary science: Bayesian analysis and link 
prediction, to enhance the current understanding of emergent temporal 
patterns in <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA), particularly in value creation through social connectedness - an
 important, and growing, discipline within management science. 
Traditional link prediction methods use the values of metrics in a graph
 to determine where new links are likely to arise, and little work has 
been done on analyzing long-term graph trends. We have found that 
existing graph generation models are unrealistic in their prediction, 
and can be complemented through the use of temporal metrics, in the 
study of some networks. To date, no temporal information has been used 
in link prediction research, thereby excluding valuable temporal trends 
that emerge in sociogram sequences and also lowering the accuracy of the
 link prediction. We extracted information from the Pussokram <font class="ScopusTermHighlight">online</font>
 dating network dataset, and 9,939 cases of each class were formed. 
Logistic regression in the Weka data mining system was used to perform 
link prediction. Our results show that temporal metrics are an extremely
 valuable new contribution to link prediction, and should be used in 
future applications. In addition to using metrics to measure the local 
behaviors of participants in social networks, we used Bayesian networks 
to model the interrelationships between the metrics as local behaviors 
and links forming between individuals as emergent behaviors (social 
complexity). We also explored how the metrics evolve over time using 
Dynamic Bayesian Networks (DBN).</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7201358969&amp;zone=" title="Show author details">Chai, C.S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7403366101&amp;zone=" title="Show author details">Tan, S.C.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=13995&amp;origin=resultslist">Teachers College Record</a></i>
111
(5)
, pp. 1296-1327
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15
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<div id="previewAbstract53"><span class="txt">Background: This study was
 situated in Singapore, which aims to achieve engaged learning in P-12 
schools with the use of educational technology. One of the foci of study
 among Singaporean educational researchers on a computer-supported 
collaborative learning (CSCL) environment that emphasizes collaboration 
among learners for the co-construction of knowledge. Although there is 
some evidence that CSCL enhances students' learning, an identified gap 
in the field of CSCL is documented accounts of how knowledge building 
happens. Knowledge of how to facilitate sustained and in-depth 
knowledge-building discourse among teachers has also been identified as a
 gap in understanding in teacher education. Purpose: This case study 
aims to gain insights into how negotiation and co-construction of 
knowledge occurs among eachers during their participation in a 
knowledge-building community. Participants: It involves 7 Singaporean 
teachers who enrolled in an 18-month Advanced Diploma program. 
Intervention: Three consecutive modules were conducted to develop the 
participants' competencies in and dispositions toward facilitating 
student-centered learning in a computer-supported collaborative learning
 (CSCL) environment. The modules engaged the teachers as coc-onstructors
 of knowledge in a knowledge-building community. Research Design: This 
is a case study in which the first author, as a participant observer, 
acted as the facilitator for the modules. Data Analysis: The main source
 of data was the teachers' notes in Knowledge Forum, a CSCL environment.
 The teachers' patterns of <font class="ScopusTermHighlight">online</font> interactions were analyzed through <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and the interaction analysis model (IAM). Findings: Our findings 
indicate that the teachers formed a socially cohesive community and 
participated rather actively, writing an average of 3.7 notes and 425 
words per week. Further analysis of the notes using IAM shows a healthy 
distribution of notes at various phases of knowledge construction. 
Conclusion: We conclude that the teacher knowledge-building community 
was successful in engaging the teachers in collaborative knowledge 
building, leading to a deep understanding among them about learning in a
 CSCL environment. We suggest the following factors as contributors to 
this advancement: (1) having a group of committed teachers as 
participants, (2) engaging the teachers to work on authentic problems 
faced in schools, (3) empowering the teachers with the agency to solve 
problems and reflect on their learning, (4) allocating adequate time for
 teachers to link theories to practice and to reflect on their 
implementation, and (5) having a facilitator who is experienced in 
facilitating this form of learning and in using a pedagogical model that
 is built on appropriate learning theories. Copyright © by Teachers 
College, Columbia University.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23992500500&amp;zone=" title="Show author details">Buchegger, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402110415&amp;zone=" title="Show author details">Datta, A.</a>
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<i>WONS 2009 - 6th International Conference on Wireless On-demand Network Systems and Services</i>
, art. no. 4801862
, pp. 161-168
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 Social Networks like Facebook, MySpace, Xing, etc. have become 
extremely popular. Yet they have some limitations that we want to 
overcome for a next generation of social networks: privacy concerns and 
requirements of Internet connectivity, both of which are due to 
web-based applications on a central site whose owner has access to all 
data. To overcome these limitations, we envision a paradigm shift from 
client-server to a peer-to-peer infrastructure coupled with encryption 
so that users keep control of their data and can use the social network 
also locally, without Internet access. This shift gives rise to many 
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<i>Proceedings - 2009 WRI International Conference on Communications and Mobile Computing, CMC 2009</i>
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<div id="previewAbstract55"><span class="txt">The study explores adolescents' <font class="ScopusTermHighlight">online</font> and offline peer social networks with the application of <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 approach. Data shows that the two social networks are significantly 
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loneliness does not correlate with any of adolescent's social network 
basic indicators. Implications of the study are discussed. © 2009 IEEE.</span></div>
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<div id="previewAbstract56"><span class="txt">To date, numerous open source projects are hosted on many <font class="ScopusTermHighlight">online</font>
 repositories. While some of these projects are active and thriving, 
some projects are either languishing or showing no development 
activities at all. This phenomenon thus begs the important question of 
what are the influential factors that affect the success of open source 
projects. In a quest to deepen our understanding of the evolution of 
open source projects, this research aims to analyze the success of open 
source projects by using the theoretical lens of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>. Based on extensive analyses of data collected from <font class="ScopusTermHighlight">online</font>
 repositories, we study the impact of the communication patterns of 
software development teams on the demand and supply outcomes of these 
projects, while accounting for project-specific characteristics. Using 
panel data analysis of data over 13 months, we find significant impacts 
of communication patterns on project outcomes over the long term. © 2009
 IEEE.</span></div>
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<div id="previewAbstract57"><span class="txt">Analysis of interaction patterns is one of the most important indicators of quality of learning in educational web forums. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) is gradually assuming importance in the study of interaction 
patterns as it focuses on the analysis of the interrelationships between
 individuals, thus providing a holistic perspective on group 
performance. However, most of the studies that use SNA in 
computer-supported collaborative learning scenarios derive their data 
from server log files, on the assumption that this data source reflects 
the way people really interacted <font class="ScopusTermHighlight">online</font>.
 This study, the purpose of which is to better understand the 
communication flows that really occur among users, challenges these 
assumptions through an experimental study that makes a comparison 
between the structural method normally used to detect the posting 
addressees and an approach enriched with semantic coding. Results show 
that this new coding schema, if compared with traditional structural 
coding, detected a greater number of addressees, thus allowing a greater
 number of postings to be included in an SNA adjacency matrix. © 2008 
Blackwell Publishing Ltd.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=13405244700&amp;zone=" title="Show author details">Caiani, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14069392700&amp;zone=" title="Show author details">Wagemann, C.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=200147110&amp;origin=resultslist">Information Communication and Society</a></i>
12
(1)
, pp. 66-109
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<div id="previewAbstract58"><span class="txt">This article applies instruments of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 to a study of communication networks within the Italian and German 
extremist right. Web links between organizational websites are used as a
 proxy. Indeed, extremist groups increasingly use and abuse the Internet
 for their propaganda and their recruitment, and also for their internal
 communication. The analysis includes both political parties and 
non-party organizations, even violent groups. In a macro-, micro-, and 
meso-analysis, the various specificities of the two national political 
sectors are demonstrated and linked to the offline reality. The Italian 
network appears to be very fragmented, highly diversified, and difficult
 to be coordinated ('policephalous network'), whereas the German network
 is denser and much more concentrated on a few central actors ('star 
structure'). These differences are mainly due to political opportunity 
structures in the two countries. Additionally, whereas the Italian 
network structure allows for the construction of a typology of 
sub-groups of organizations, the German communicative structure seems to
 be more erratic and less coordinated. The article also highlights the 
function of websites which are not related to any specific group. 
Indeed, these are of special importance for the far right as a political
 arena which is usually banned from the dominant societal discourses (if
 not even legally forbidden). Considering this, new modes of 
communication can be of greater use for extremist groups than for more 
traditional political actors.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36845784700&amp;zone=" title="Show author details">Schlager, M.S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14052047500&amp;zone=" title="Show author details">Farooq, U.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7003377278&amp;zone=" title="Show author details">Fusco, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6507147517&amp;zone=" title="Show author details">Schank, P.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14832770000&amp;zone=" title="Show author details">Dwyer, N.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=13354&amp;origin=resultslist">Journal of Teacher Education</a></i>
60
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<div id="previewAbstract59"><span class="txt">The authors argue that 
conceptual and methodological limitations in existing research 
approaches severely hamper theory building and empirical exploration of 
teacher learning and collaboration through cyber-enabled networks. They 
conclude that new frameworks, tools, and techniques are needed to 
understand and maximize the benefits of teacher networks. The paper 
presents preliminary data to illuminate both the power and limitations 
of current tools and techniques for studying cyber-enabled networks 
using data from a large, mature <font class="ScopusTermHighlight">online</font>
 network of K-12 educators. The findings raise fundamental questions 
that are beyond the capability of most education researchers and 
evaluators to address rigorously and cost-effectively. The authors 
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generation of research tools and techniques that enable researchers ask 
more incisive and convergent research questions and help school leaders 
and teachers support, learn, and collaborate with one another more 
effectively in cyber-enabled professional communities. © 2009 Sage 
Publications.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7601351820&amp;zone=" title="Show author details">Zhang, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6506592725&amp;zone=" title="Show author details">Scardamalia, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24575034000&amp;zone=" title="Show author details">Reeve, R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16646575000&amp;zone=" title="Show author details">Messina, R.</a>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=13357&amp;origin=resultslist">Journal of the Learning Sciences</a></i>
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<div id="previewAbstract60"><span class="txt">This article reports a 
design experiment conducted over three successive school years, with the
 teacher's goal of having his Grade 4 students assume increasing levels 
of collective responsibility for advancing their knowledge of optics. 
Classroom practices conducive to sustained knowledge building were 
co-constructed by the teacher and students, with Knowledge Forum 
software supporting the production and refinement of the community's 
knowledge. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> and qualitative analyses were used to assess <font class="ScopusTermHighlight">online</font>
 participatory patterns and knowledge advances, focusing on indicators 
of collective cognitive responsibility. Data indicate increasingly 
effective procedures, mirrored in students' knowledge advances, 
corresponding to the following organizations: (a) Year 1 - fixed 
small-groups; (b) Year 2 - interacting small-groups with substantial 
cross-group knowledge sharing; and (c) Year 3 - opportunistic 
collaboration, with small teams forming and disbanding under the 
volition of community members, based on emergent goals. The third-year 
model maps most directly onto organic and distributed social structures 
in real-world knowledge-creating organizations and resulted in the 
highest level of collective cognitive responsibility, knowledge 
advancement, and dynamic diffusion of information. Pedagogical and 
technological innovations to enculturate youth into a knowledge-creating
 culture, with classroom practices to encourage distributed and 
opportunistic collaboration, are discussed.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402284022&amp;zone=" title="Show author details">Hsu, J.-L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7202063836&amp;zone=" title="Show author details">Chou, H.-W.</a>
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2009</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=145056&amp;origin=resultslist">International Journal of Distance Education Technologies</a></i>
7
(1)
, pp. 1-22
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<div id="previewAbstract61"><span class="txt">With increasing 
convenience and prevalence, the distant communication application has 
become a promising way for individuals who are eager to cooperate and 
interact virtually. This study explored the question of whether the 
collaborative interaction of the virtual teams has any effect on the 
conflict and network structure of virtual groups. A total of 150 
participants were invited and randomly assigned to thirty groups with 
each group of five subjects. To function like real virtual groups, they 
were asked to communicate with their members through e-mail. Through 
genre analysis and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 nine communicative genres most frequently used in the collaborative 
groups were identified. Results of correlation analysis suggested that 
it was the communicative genres, not the network structure, that were 
associated with intra-group conflict of virtual group. Accordingly, 
whether the network structure of the virtual group is centralized or 
decentralized may not be instructors' or developers' major concern. 
Instead, they may wish to focus on a well-designed interface providing 
needed supports of communicative procedure for coordinating with distant
 members. Copyright © 2009.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23392716500&amp;zone=" title="Show author details">Karamon, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55101964900&amp;zone=" title="Show author details">Matsuo, Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35475985500&amp;zone=" title="Show author details">Ishizuka, M.</a>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=78337&amp;origin=resultslist">Proceedings of the National Conference on Artificial Intelligence</a></i>
2
, pp. 1162-1168
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<div id="previewAbstract62"><span class="txt">Recently, many Web 
services such as social networking services, blogs, and collaborative 
tagging have become widely popular. Many attempts are being made to 
investigate user interactions by analyzing social networks among users. 
However, analyzing a social network with attributional data is often not
 an easy task because numerous ways exist to define features through 
aggregation of different tables. In this study, we propose an algorithm 
to identify important network-based features systematically from a given
 social network to analyze user behavior efficiently and to expand the 
services. We apply our method for link-based classification and link 
prediction tasks with two different datasets, i.e., an @cosme (an <font class="ScopusTermHighlight">online</font>
 viral marketing site) dataset and a Hatena Bookmark (collaborative 
tagging service) dataset, to demonstrate the usefulness of our 
algorithm. Our algorithm is general and can provide useful network-based
 features for <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analyses</font>. Copyright © 2008, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6506967497&amp;zone=" title="Show author details">Adamic, L.A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35239357700&amp;zone=" title="Show author details">Zhang, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25824656600&amp;zone=" title="Show author details">Bakshy, E.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7102657846&amp;zone=" title="Show author details">Ackerman, M.S.</a>
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2008</div>
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<i>Proceeding of the 17th International Conference on World Wide Web 2008, WWW'08</i>
, pp. 665-674
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<div id="previewAbstract63"><span class="txt">Yahoo Answers (YA) is a 
large and diverse question-answer forum, acting not only as a medium for
 sharing technical knowledge, but as a place where one can seek advice, 
gather opinions, and satisfy one's curiosity about a countless number of
 things. In this paper, we seek to understand YA's knowledge sharing 
activity. We analyze the forum categories and cluster them according to 
content characteristics and patterns of interaction among the users. 
While interactions in some categories resemble expertise sharing forums,
 others incorporate discussion, everyday advice, and support. With such a
 diversity of categories in which one can participate, we find that some
 users focus narrowly on specific topics, while others participate 
across categories. This not only allows us to map related categories, 
but to characterize the entropy of the users' interests. We find that 
lower entropy correlates with receiving higher answer ratings, but only 
for categories where factual expertise is primarily sought after. We 
combine both user attributes and answer characteristics to predict, 
within a given category, whether a particular answer will be chosen as 
the best answer by the asker.</span></div>
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2008</div>
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<i>Proceedings of the Conference on Integrating Technology into Computer Science Education, ITiCSE</i>
, art. no. 1384384
, pp. 342
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<div id="previewAbstract64"><span class="txt">Active Learning in 
Computing (ALiC) is the first Centre for Excellence in Teaching and 
Learning (CETL) project for Computing Science in England. Funded by 
HEFCE, the initiative seeks to prepare students for the realities of 
working in their chosen field by aligning their learning experiences and
 transferable skill sets with those sought by today's software 
engineering industry. One way ALiC achieves this is by introducing 
cross-site, collaborative group-programming tasks into the curriculum. 
Running over an academic year, this approach encourages active 
interaction and dialogue between student teams at Newcastle and Durham 
universities, and develops strong, real-world problem solving skills in 
participants. The ALiC project has thus far generated a great deal of 
positive feedback from undergraduates, and we feel our approach to 
inter-institutional teamwork offers students a realistic and relevant 
"real world" experience [2]. However, we are also becoming increasingly 
aware that time and resource pressures can make it difficult for 
students to maintain adequate levels of communication for any length of 
time [4], and once a team disperses it becomes difficult for its members
 to preserve the channels needed to interact and collaborate 
effectively. Consequently, an emerging area of research at Newcastle 
University concerns how learning can be enhanced through the use of 
computer-mediated social networking environments -<font class="ScopusTermHighlight">online</font>
 communities such as Facebook, Friendster and Bebo -through which 
registered users connect with friends and colleagues to explore similar 
interests and activities. In a collaborative educational context, these <font class="ScopusTermHighlight">online</font>
 social networking services offer an attractive means to foster student 
interaction and community building by providing a means to explore the 
common ground that exists between participants [1]. To that end, we 
intend to embed the communication and "social awareness" affordances - 
profile creation, synchronous and asynchronous chat, status updates, 
etc. - of popular social networking sites into our undergraduate, 
cross-site software engineering projects [3]. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 will be used to identify, map and analyse the flow of information and 
resources between distributed team members. The pedagogic motivation 
behind this work is to foster greater group-oriented interaction by 
filling the communication void that often arises between face-to-face 
meetings [5]. By reducing the geographic and temporal barriers to 
interaction and community formation (especially where 'peripheral', 
passive team members are concerned), team members will become 
increasingly aware of each others' skills, personalities, work rhythms 
and needs - both <font class="ScopusTermHighlight">online</font> and off - within a pre-existing, persistent, convenient infrastructure.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7202143742&amp;zone=" title="Show author details">Santos, E.E.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23980706000&amp;zone=" title="Show author details">Santos Jr., E.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35316429700&amp;zone=" title="Show author details">Pan, L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26421527300&amp;zone=" title="Show author details">Wilkinson, J.T.</a>
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2008</div>
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<i>Proceedings of the 2008 International Conference on Artificial 
Intelligence, ICAI 2008 and Proceedings of the 2008 International 
Conference on Machine Learning; Models, Technologies and Applications</i>
, pp. 449-455
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<div id="previewAbstract65"><span class="txt">Social networks are an 
important way to represent and analyze social phenomena. One aspect that
 is critical in order to provide relevant and useful analyses is the 
capability to infuse culture systematically. Cultural elements are 
typically either lacking or implicitly (and sometimes unintentionally) 
embedded in social network construction. Thus, current SNA approaches 
must deal with imprecise, un-realistic, and incomplete data. In this 
paper, we propose a generic approach to systematically model culture and
 infuse it into social networks to obtain more realistic and complete 
social network data sets that can provide insight into the probable 
intentions and behaviors of the actors in the network. In fact, in this 
paper we will introduce the concept of culturally-infused social 
networks, their construction, and their capability to provide fuller and
 more relevant <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analyses</font>.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36981818900&amp;zone=" title="Show author details">Kim, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35991389000&amp;zone=" title="Show author details">Barnett, G.A.</a>
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2008</div>
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<i>14th Americas Conference on Information Systems, AMCIS 2008</i>
5
, pp. 2827-2835
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<div id="previewAbstract66"><span class="txt">This study examines the 
social network of scholars in the field of Communication by using author
 co-citation data. A matrix containing the number of co-cited documents 
between pairs of authors is created for <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 of scholars who are on the editorial board of Journal of Communication,
 and the networked map of the scholars is used to visualize the 
knowledge structure of the field by identifying groups of authors who 
are more central than others. Social Science Citation Index (SSCI) is 
used to collect the author co-citation data, and UCInet is employed for <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> as well as network visualization.</span></div>
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 network analysis applied to knowledge creation and transfer in the 
portuguese agricultural R&amp;D field: An exploratory study</a>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=49864133900&amp;zone=" title="Show author details">Neto, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24346356100&amp;zone=" title="Show author details">Correia, A.M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15735967400&amp;zone=" title="Show author details">Pinto, P.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55486970100&amp;zone=" title="Show author details">Aguiar, J.</a>
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2008</div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 585-593
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<div id="previewAbstract67"><span class="txt">There is growing interest 
in the nature and scale of scientific collaboration regarding the 
processes involved with knowledge creation and sharing. One of the 
possible approaches to developing metrics for this area of research is 
based on the idea that co-authorship creates a social network of 
researchers. We present an exploratory study using a social network 
approach to examine the structure and pattern of knowledge creation and 
sharing within a Portuguese research community, working in the 
agricultural field, over the last seven years. The members of this 
community are with the Instituto Nacional da Investigação Agrária (INIA)
 which recently became part of a newly created R &amp; D State 
Laboratory, Instituto Nacional dos Recursos Biológicos (INRB), under the
 umbrella of the Portuguese Ministry of Agriculture Rural Development 
and Fisheries. The <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 used data from an information system containing the results from all 
the scientific activities developed in the last seven years by the 
research community working in INIA. The information system was the major
 result of AGRO 444 - Development of an Information System for Knowledge
 and Innovation Discovery and Diffusion in the Agro-Rural Sector, a 
project funded by Measure 8.1 of Programa AGRO, one of the policy 
instruments of "3° Quadro Comunitário de Apoio" (Third European 
Framework Aid to Portugal, 2000- 2006). From this data, a knowledge 
network was developed based on co-authorship patterns extracted from the
 information system, covering the period 2000-2006. This knowledge 
network supported the analysis of specific paths through which knowledge
 sharing occurred and by which knowledge capital was nurtured within the
 agricultural R &amp; D activities of this institution.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55489605700&amp;zone=" title="Show author details">Mueller, C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8554946700&amp;zone=" title="Show author details">Gronau, N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36721282700&amp;zone=" title="Show author details">Lembcke, R.</a>
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2008</div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract68"><span class="txt"><font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) is increasingly applied to analyze existing knowledge exchange 
processes in companies. In the past, these processes were mainly 
analyzed by traditional business process modeling methods. Same of these
 methods are working with a specific knowledge perspective, e.g. KMDL 
(Knowledge Modeling and Description Language). The knowledge needs and 
demands are modeled along knowledge-intensive business processes. The 
SNA however has no direct reference to processes; here persons with 
specific relationships (e.g. knowledge exchange) are mainly the object 
of interest. Therefore a combination of both views - the SNA and 
knowledge-intensive business process modeling - is valuable. In the 
following contribution two approaches are introduced to combine <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 with the modeling of knowledge intensive business processes based on 
KMDL. In addition to a theoretical introduction to SNA and KMDL there 
are two examples introduced, which illustrate the practical 
implementation of these approaches. In this work in progress traditional
 techniques like interviews are combined with electronically gathered 
data. Also by using different perspectives a better understanding of all
 events in knowledge processes can be extracted.</span></div>
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<i>13th International Conference of the Association Information and Management 2008, AIM 2008</i>
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<div id="previewAbstract69"><span class="txt">The major feature 
introduced by the « open source model », is a transformation of the 
value, from the classic IPR, and the commercial licences, to a model 
based on an accurate service around a source code freely available and 
shared by a community. This point is problematic for the constitution of
 new business models, and the economic literature mainly focus on this 
aspect. The second effect is that, this centrality on the code, breed a 
particular attention on the people who create it: the open source 
developers. They now became on the center of the strategy of open source
 companies. The aim of this study is to show, the impact of open source,
 on the carrier constitution of those developers. To do this. We have 
done an exhaustive <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 of a major open source project, in which we have extracted from CVS 
(Control Visioning System) the social network graphs of relation between
 participants, for every year, from 1996, the beginning of the project 
up to 2007. We correlated those social network longitudinal data, with 
the resumes of the participants collected on the web and for every year 
we added elements about the organization, the occupation and the 
location of those developers. Thus we see emerging many common aspects 
in those carreers, on the way of being involve in open source, the way 
they get a job within the industry, the emerging of central companies, 
and the way developers are hired by them. From this quantitative and 
qualitative analysis, we see that, becoming an open source developer, is
 the result of a particular learning and cultural trajectory and that 
this trajectory is as individual as entrepreneurial.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=16719&amp;origin=resultslist">Proceedings - Frontiers in Education Conference, FIE</a></i>
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<div id="previewAbstract70"><span class="txt">The general available tools for analyzing interactions in <font class="ScopusTermHighlight">online</font>
 discussion forums appear to be insufficient to characterize groups of 
medium/large dimensions, as they are limited to provide general 
information of participation, access statistics and message posting. Our
 research contributes for analyzing and characterizing asynchronous <font class="ScopusTermHighlight">online</font> interactions applying the <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 methodology, by providing e-learning platforms with an interactive 
graph - the iGraph - that illustrates, and analyses, students' 
interactions. In a graphical interface embedded in an open source 
learning management system we combine real-time graphs and numerical 
indicator to provide the educator with a more thorough understanding of 
relations between course participants. Preliminary results indicate that
 the iGraph enables an insightful characterization of the interactions 
between actors and their participations in discussion forums. © 2008 
IEEE.</span></div>
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<i>Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education, ITME 2008</i>
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<div id="previewAbstract71"><span class="txt">Cohesion is one of key factors influencing the performance of collaborative learning. But it is hart to reckon and assess it in <font class="ScopusTermHighlight">online</font> collaborative learning environments. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) is a new method and technique analyzing the properties of the 
interaction relations between participants. In this paper, we introduced
 the related key concepts in SNA, and presented an analysis model which 
can analyze the cohesion of groups effectively and precisely, and then 
showed a case study which was from a quasi-experiment in our instruction
 practice, lastly, drew several useful principles on reckoning cohesion 
in <font class="ScopusTermHighlight">online</font> collaborative learning by SNA. © 2008 IEEE.</span></div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract72"><span class="txt">This paper introduces a new Web mining approach that combines <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and automatic sentiment analysis. We show how weighting the forum posts
 of the contributors according to their network position allow us to 
predict trends and real world events in the movie business. To test our 
approach we conducted two experiments analyzing <font class="ScopusTermHighlight">online</font>
 forum discussions on the Internet movie database (IMDb) by examining 
the correlation of the social network structure with external metrics 
such as box office revenue and Oscar Awards. We find that discussion 
patterns on IMDb predict Academy Awards nominations and box office 
success. Two months before the Oscars were given we were able to 
correctly predict nine Oscar nominations. We also found that forum 
contributions correlated with box office success of 20 top grossing 
movies of 2006.</span></div>
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<i>Proceedings - 4th IEEE International Conference on eScience, eScience 2008</i>
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<div id="previewAbstract73"><span class="txt">Many scientists maintain blogs and participate in <font class="ScopusTermHighlight">online</font> communities through their blogs and other scientists' blogs. This study used <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> methods to locate and describe <font class="ScopusTermHighlight">online</font>
 communities in science blogs. The structure of the science blogosphere 
was examined using links between blogs in blogrolls and in comments. By 
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 easily found. Using spin glass community detection, six cohesive 
subgroups loosely corresponding to subject area were found. By commenter
 links, the blogs form into more easily findable general subject area or
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<i>Proceedings - 2008 IEEE/WIC/ACM International Conference on Web 
Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 
Workshops 2008</i>
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healthcare service in Western Australia. © 2008 IEEE.</span></div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract77"><span class="txt">Despite their enormous success the motivation behind user participation in <font class="ScopusTermHighlight">Online</font>
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<i>Proceedings - ICCE 2008: 16th International Conference on Computers in Education</i>
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<div id="previewAbstract78"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 learning is often supported by technologies that provide task-oriented 
groups such as classes or professional development teams with their own 
workspaces for interaction. This paper begins an exploration into the 
proposition that participants may benefit if they are not isolated from 
each other, but rather are enabled to discover persons and resources 
from contexts other than the original context to which they were 
assigned. The potential value that resides in technology-supported 
social networks has been called socio-technical capital. Our software, 
Prometheus, is being used to support <font class="ScopusTermHighlight">online</font>
 university level education and teacher professional development under 
an open community model inspired by this idea. The analysis reported in 
this paper tests whether people who come to the <font class="ScopusTermHighlight">online</font>
 environment for instrumental objectives such as taking a course 
encounter persons or products of others from outside their immediate 
workspace, and also seeks to identify how the various digital media 
available in Prometheus support these encounters. Results show distinct 
roles for each of discussions, resources, user profiles, and wiki pages,
 and point the way to further work.</span></div>
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<i>Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008</i>
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, art. no. 4722863
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<div id="previewAbstract79"><span class="txt">Social relations are of great importance in <font class="ScopusTermHighlight">online</font>
 collaborative learning. As the interface between behaviors and 
contexts, conceptions of social relations decide how a learner deals 
with social relations in a certain context. However, the prevalent 
research approach of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) in the study of social relations offers little insight into this 
aspect. This leads the authors to explore conceptions of social 
relations in <font class="ScopusTermHighlight">online</font> collaborative learning with a phenomenographic approach in a case study of China higher education learners of an <font class="ScopusTermHighlight">online</font>
 course "Introduction to e-Learning". This paper reports on the results 
of the study, which discovers three conceptual categories namely 
learner-learner relationship, learner-tutor relationship, and group 
tension with hierarchical features in each category. © 2008 IEEE.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24831578800&amp;zone=" title="Show author details">Kowatsch, T.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7005129380&amp;zone=" title="Show author details">Maass, W.</a>
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2008</div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract80"><span class="txt">Collaborative indexing 
systems have attracted an increasing amount of attention over the last 
three years. One fundamental limitation to such a system is the 
uncontrolled nature of its vocabulary, as this consists of terms users 
freely choose to index resources. As a result, the vocabulary can be 
poorly structured, making it difficult to harvest knowledge from the 
user community. Pre-defined terms are suggested to reduce this 
uncontrolled vocabulary. However, this suggestion has not yet been 
proven. This work therefore focuses on an empirical study of the 
adoption of pre-defined terms and its impact on the community's 
vocabulary by implying innovation diffusion theory. A research model is 
formulated to explain the relationship between the degree of adoption 
and its impact on the vocabulary in order to indicate consolidated term 
usage. For this purpose, constructs of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 are applied. The model is then validated by one lab experiment (n=172),
 before being cross-validated by two open web experiments (n=254, 
n=160). Results indicate that to a remarkable extent, pre-defined terms 
are appropriate for reducing the uncontrolled nature of the community's 
vocabulary, such that the utility of collaborative indexing systems can 
be increased.</span></div>
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2008</div>
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<i>ICIS 2008 Proceedings - Twenty Ninth International Conference on Information Systems</i>
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<div id="previewAbstract81"><span class="txt">The use of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) in the design of expert recommendation systems is becoming 
increasingly popular. However, the experts recommended from such systems
 often do not meet users' needs since the network semantic information 
is largely ignored. In this study, we used conditional logistic analysis
 to quantitatively examine the semantics of two social networks in a 
large open source community called Ohloh. It was found that homophily in
 nationality, location, programming language preference, and community 
reputation are determinants for forming evaluation and collaboration 
relationships among the Ohloh members. Moreover, past collaborations and
 mutual acquaintances are also found to significantly affect the 
formation of evaluation links but not collaboration links. In addition, 
we demonstrated how to embed the discovered network semantics into the 
design of expert recommendation systems through two mechanisms - 
user-based link prediction and Top-N most recognized mechanism.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=13410539800&amp;zone=" title="Show author details">Smyth, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603787961&amp;zone=" title="Show author details">Pryke, S.</a>
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2008</div>
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<i>COBRA 2008 - Construction and Building Research Conference of the Royal Institution of Chartered Surveyors</i>
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<div id="previewAbstract82"><span class="txt">This paper explores the 
linkage between three important areas in the management of project 
delivery organisations: (i) the exploration of relationship strength in 
social networks of clients, (ii) the application of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 as a research method to this area, (iii) operationalising the research 
to produce practical and theoretical outputs for evaluating (implicit 
and explicit) relationship practices within the relationship 
marketing/management paradigm. The exploration builds upon the work of 
Q-Industries, a website and business application developer, who have 
linked two conceptual areas in practice: Client Relationship Management 
(CRM) and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> (SNA). CRM software has its origins in relationship marketing. Developing an open-source CRM Platform applying principles of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 for Odell, Simms &amp; Associates, a fundraising and economic 
development firm, has allowed visual mapping and identification of 
relationships, hence how the people connect within a network 
(www.prweb.com/releases/2007/11/prweb566467.htm - accessed 27/02/08). 
CRM systems are typically software and hardware based and the nature of 
networks is opaque or unseen. The challenge in this paper is to work 
back from the practice and work forward from the concepts to explore how
 the same principles can be methodologically established in 
organisational management systems (socio-psychological rather than 
technical) for empirical investigation. © RICS.</span></div>
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2008</div>
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<i>14th Americas Conference on Information Systems, AMCIS 2008</i>
5
, pp. 2805-2814
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<div id="previewAbstract83"><span class="txt">The present study 
describes an Integrated Methodology developed combining Social Network 
and Content Analysis approaches, to investigate the organizational 
mechanisms responsible for the creation of Social Capital within 
Communities. The methodological integration is proposed to overcome one 
of the main limitations of <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA): the analysis of the content of the information flows and the 
organizational and cultural aspects of their exchanges. The 
methodological framework was able to differentiate the "ties" among 
community members on the basis of the subject matter of the information 
flows. It showed its reliability for Project-oriented Virtual 
Communities to discover and draw the development path of their projects,
 from the new idea generation to the project outcome delivery, through 
the content "tagging of the information flows. It is suitable to 
describe the main characteristics of a project-oriented community, 
useful and effective to monitor the processes developed within the 
community.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23669229400&amp;zone=" title="Show author details">Suh, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=21735905700&amp;zone=" title="Show author details">Shin, K.-S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15836395400&amp;zone=" title="Show author details">Bock, G.-W.</a>
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2008</div>
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<i>PACIS 2008 - 12th Pacific Asia Conference on Information Systems: 
Leveraging ICT for Resilient Organizations and Sustainable Growth in the
 Asia Pacific Region</i>
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<div id="previewAbstract84"><span class="txt">This study deals with the 
relationship between the project team's social network and knowledge 
accessibility from an empirical aspect. What kind of network structure 
is desirable to improve project team members' knowledge accessibility? 
Does a strong connection among group members improve their knowledge 
accessibility? Otherwise, does the expansion of the external network of a
 group improve its members' knowledge accessibility more efficiently? 
This study aims to contribute to developing existing network theories 
and knowledge management theories by answering these questions. To solve
 the raised research questions, a multi-level research model was 
developed on the basis of social network theory. From a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 which was conducted on 172 consultants and 42 project teams in 5 global
 consulting companies in Korea, it was found that the research results 
backed the existing two different social network mechanisms: closure 
mechanism and brokerage mechanism. However, the effect of social network
 on knowledge accessibility of project team members varied along the 
type of network involved. This study is meaningful in that it overcame 
the limits of the unit of analysis shown in existing studies by 
distinguishing group-level network density from individual-level network
 properties, and by analyzing the moderating effect between them.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=26424533300&amp;zone=" title="Show author details">Berger, S.C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14033045500&amp;zone=" title="Show author details">Hinz, O.</a>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract85"><span class="txt">The question for the effectiveness of inter-organizational collaboration gains much attraction in the light of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 We analyze this by the case of Initial Public Offering (IPO) deal 
networks as this is a valuable example for the repeated collaboration of
 autonomous organizations on a shared goal and data is publicly 
available. We use the social networks established through deal 
activities over time as independent variables explaining the success of 
the IPO. Although we did not find statistically significant support for 
the impact of centrality for neither the lead manager nor the consortium
 banks, we see that the clustering among the consortium banks is a 
significant driver for IPO success. The higher the clustering amongst 
the collaborating consortium banks the better the performance of the 
issued share. We thereby provide initial evidence for the influence of 
network structure on IPO success and show that the build-up of the 
consortium has a significant impact on the success of the IPO. In terms 
of methodology, we explore a way of constructing networks from previous 
collaborations which form the basis for proven analysis techniques and 
might help to shed light on various questions in the domain of 
inter-organizational collaboration.</span></div>
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1086
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55489705200&amp;zone=" title="Show author details">Hamre, L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603402952&amp;zone=" title="Show author details">Vidgen, R.</a>
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2008</div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract86"><span class="txt">Information System (IS) 
implementations are a risky business with studies showing only a 16% - 
29% success rate. This research explores the use of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) to inform the creation of a Community of Practice (CoP) to 
support a Finance Management System implementation in a higher education
 organization. IS implementations can be equated to the diffusion of 
innovation. The successful diffusion of an innovation requires it to be 
communicated through a social system. Organizations rarely know what 
their social network looks like - it is not the formal organization 
chart. SNA can be used to gain an understanding of the social network 
and how individuals with high social capital can be identified. There is
 growing evidence that CoP support successful organizational change 
initiatives but it is less clear how CoP membership might be agreed. SNA
 provides an evidence-based approach to CoP formation. The IS 
implementation case described in the paper demonstrates a new approach 
to IS implementation grounded in social capital and CoP and illustrates 
how it might be conducted in practice.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55487105000&amp;zone=" title="Show author details">Omasits, D.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15070762300&amp;zone=" title="Show author details">Noll, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=11440526100&amp;zone=" title="Show author details">Hörlesberger, M.</a>
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2008</div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 625-634
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<div id="previewAbstract87"><span class="txt">Knowledge is an essential 
resource for most of today's organisations. Therefore high efforts are 
taken to implement highly effective and efficient knowledge-based 
processes. During the last 20 years, not only the huge potential of 
different knowledge management measures but also different drawbacks 
have become obvious. Scientists and practitioners are still working on 
analysing factors that influence the successful implementation of 
knowledge management tools and to find ways to measure its effectiveness
 in organisations. One tool that gains increasing importance in 
knowledge-intensive organisations are Communities of Practice (CoPs). 
CoPs are informal groups of people with a common interest to exchange 
knowledge concerning a specific topic. Therefore they are highly 
applicable for identifying, sharing, developing and saving explicit and 
tacit knowledge. Practical experience has shown that CoPs are one of the
 most effective tools to support organisational learning but at the same
 time one of the most difficult ones. Based on their potential for 
experience exchange and spreading excellence, arsenal research decided 
to develop CoPs as a strategic management tool. Special emphasis is 
given the cultivation of a collaborative and innovative working 
environment that cross-links its multidisciplinary research staff and by
 that supports knowledge transfer and increases knowledge efficiency. 
The CoPs are up and running for two years and the experiences made up to
 now will be summarized. The CoPs are continuously monitored and 
evaluated by a knowledge management team. For evaluating the 
effectiveness and the impacts of the Communities a <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA), based on a quantitative questionnaire, was performed twice - 
first in the starting phase of the Communities and second after about 18
 months operating time. The results of these two SNAs indicated that the
 Communities have indeed contributed to a better linkage of the 
scientists. Nevertheless the communities have still to be improved to 
gain better knowledge efficiency within the entire organisation. To 
identify the main influencing factors on the CoPs the corporate culture 
was analysed, focusing especially on the strength of corporate culture. 
Based on qualitative interviews factors supporting and hindering the 
CoPs have been identified and different options to positively influence 
cooperation and communication between different business fields and 
within the Communities were recommended.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=22235363800&amp;zone=" title="Show author details">Riemer, K.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7801493688&amp;zone=" title="Show author details">Vom Brocke, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=37000398300&amp;zone=" title="Show author details">Richter, D.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55489973900&amp;zone=" title="Show author details">Große Böckmann, S.</a>
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2008</div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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<div id="previewAbstract88"><span class="txt">University research is 
increasingly organised in inter-organisational networks. As part of its 
6th research framework, the European Commission (EC) funded a total of 
130 so called networks of excellence (NoEs), a special kind of network 
with the purpose of strengthening and developing community, scientific 
and technological excellence by way of integrating existing and emerging
 research activities and by exchanging knowledge. In such NoEs 
electronic collaboration platforms are typically implemented to support 
collaboration between the individuals from the various research 
institutions. In this paper we investigate the adoption of a 
collaboration platform in one NoE case - the GARNET network. We find 
evidence that the platform is used for administrative purposes and to 
support the organisation of events. However, a web log analysis reveals a
 lack of adoption for its actual purpose - the support of collaborative 
research and knowledge exchange. A <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 further uncovers that the GARNET network is very fragmented on the 
social level, which points to a misfit between network structure and the
 positioning of the collaboration platform. Our findings lead us to 
suggest immediate next steps for this NoE and also point to general 
implications for network designers and future research in the domain.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23012636500&amp;zone=" title="Show author details">Ma, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16240261600&amp;zone=" title="Show author details">Yang, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7006811415&amp;zone=" title="Show author details">Lyu, M.R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7102275781&amp;zone=" title="Show author details">King, I.</a>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=55826&amp;origin=resultslist">International Conference on Information and Knowledge Management, Proceedings</a></i>
, pp. 931-940
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<div id="previewAbstract89"><span class="txt">Data sparsity, scalability
 and prediction quality have been recognized as the three most crucial 
challenges that every collaborative filtering algorithm or recommender 
system confronts. Many existing approaches to recommender systems can 
neither handle very large datasets nor easily deal with users who have 
made very few ratings or even none at all. Moreover, traditional 
recommender systems assume that all the users are independent and 
identically distributed; this assumption ignores the social interactions
 or connections among users. In view of the exponential growth of 
information generated by <font class="ScopusTermHighlight">online</font> social networks, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 is becoming important for many Web applications. Following the 
intuition that a person's social network will affect personal behaviors 
on the Web, this paper proposes a factor analysis approach based on 
probabilistic matrix factorization to solve the data sparsity and poor 
prediction accuracy problems by employing both users' social network 
information and rating records. The complexity analysis indicates that 
our approach can be applied to very large datasets since it scales 
linearly with the number of observations, while the experimental results
 shows that our method performs much better than the state-of-the-art 
approaches, especially in the circumstance that users have made few or 
no ratings. Copyright 2008 ACM.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24068626200&amp;zone=" title="Show author details">Biddix, J.P.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25641238200&amp;zone=" title="Show author details">Han Woo Park</a>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=16306&amp;origin=resultslist">New Media and Society</a></i>
10
(6)
, pp. 871-891
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<div id="previewAbstract90"><span class="txt">Contemporary information 
and communication technologies (ICTs) have given rise to networked 
communities useful in organizing, coordinating, supporting and 
maintaining 'real life' activism. This article examines the campus 
living wage movement among college students in the United States to 
identify a networked activist community, its key components and the 
consequences for its members. A refinement of Howard's network 
ethnography approach serves as a mixed methods design strategy. A 
network analysis of hyperlinks revealed the structure of the network, 
while member interviews were used to discuss the importance of such 
connections. The findings revealed the importance of ICTs in maintaining
 a movement through the creation of an unintentional networked community
 in times of both mobilization and latency. Notably, the resultant 
network has allowed the campus living wage movement to overcome previous
 limitations inherit in student protest, and sustained the campus 
struggle through several student generations. © 2008 SAGE Publications.</span></div>
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2008</div>
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<i>16th European Conference on Information Systems, ECIS 2008</i>
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0
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<div id="previewAbstract91"><span class="txt">Social network sites count
 millions of members these days. For a growing number of Internet users,
 maintaining a profile on a social network site is part of their 
everyday life today. The debate of the social use of the Internet has 
focused on the one hand, on whether persons establish new relationships <font class="ScopusTermHighlight">online</font>
 and, on the other hand, on how persons use the Internet to maintain 
relationships. Social network sites explicitly aim at supporting people 
in both aspects. The number of members shows their success, but do 
social network sites really afford the maintenance of existing and 
establishment of new contacts? As yet, there has been no systematic 
investigation of the motivations and usage patterns on social network 
sites. This study lays the groundwork describing the social networks 
displayed as well as the perceptions members have of the displayed 
connections between others. Furthermore, the frequency, motivations and 
outcome of the creation of links to yet unknown persons are 
investigated. Participants of a German SNS were surveyed with an <font class="ScopusTermHighlight">online</font>
 questionnaire. The results show rather small networks which consist of 
both work and private contacts suggesting a substantial overlap with the
 offline networks. Regarding new links, over half of the users have 
added an as yet unknown person to their contact list, but many of new 
relationships do not develop further.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8963143000&amp;zone=" title="Show author details">Hu, D.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55497354500&amp;zone=" title="Show author details">Leon Zhao, J.</a>
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2008</div>
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<i>14th Americas Conference on Information Systems, AMCIS 2008</i>
6
, pp. 3484-3491
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<div id="previewAbstract92"><span class="txt">The open source software 
(OSS) development communities have experienced rapid growth in recent 
years. Previous social network studies on OSS communities focused on 
collaboration relationships. However, information about how OSS 
community members perceive each other is largely ignored. In this study,
 we report an empirical investigation of the evaluation network in an <font class="ScopusTermHighlight">online</font>
 OSS community which includes over 11,800 OSS projects and more than 
94,330 developers. A collaboration network is modeled from this data set
 and analyzed for comparison purposes. We find the evaluation network is
 significantly different from collaboration network in average degree, 
average path length and fragmentation rate. Furthermore, we argue that 
the evaluation networks can be used to locate expertise - skillful 
developers in OSS communities and capture important social relationships
 among the developers missed in the collaboration network. These 
characteristics of the evaluation network may benefit the research of 
OSS development communities and expert recommendation systems.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23391691900&amp;zone=" title="Show author details">Enkhsaikhan, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36078712200&amp;zone=" title="Show author details">Liu, W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7202326872&amp;zone=" title="Show author details">Reynolds, M.</a>
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2008</div>
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<i>PACIS 2008 - 12th Pacific Asia Conference on Information Systems: 
Leveraging ICT for Resilient Organizations and Sustainable Growth in the
 Asia Pacific Region</i>
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<div id="previewAbstract93"><span class="txt">Knowledge discovery from 
large data collection is increasingly important for knowledge-intensive 
information systems. In addition, effective visualisation are vital for 
understanding the knowledge embedded in the data. This paper aims to 
identify specific named entities from structured text content and 
visualise them in terms of social relations and geographical locations. 
The system presented here retrieves author information from publication 
data, disambiguates people names and creates a graph that visualises the
 co-author connections in order to build co-author networks for a 
specified topic in a given time period. Each co-author connection at a 
different time is shown using a coloured line to effectively visualise 
the co-author relations over time. The system also retrieves addresses 
of organizations for authors and displays them on a geographical map. 
Thus, the places that concentrate on a specific research topic for a 
given time period are geographically identfied. The paper presents an 
effective way to discover and visualise social networks of authors and 
geographical locations of researchers on a particular topic.</span></div>
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2008</div>
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<div id="previewAbstract94"><span class="txt">The goal of this research 
is to facilitate the design of systems which will mine and use 
sociocentric social networks without infringing privacy. We describe an 
extensive experiment we conducted within our organization comparing 
social network information gathered from various intranet public sources
 with social network information gathered from a private source - the 
organizational email system. We also report the conclusions of a series 
of interviews we conducted based on our experiment. The results shed 
light on the richness of public social network information, its 
characteristics, and added value over email network information. 
Copyright 2008 ACM.</span></div>
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<i>14th Americas Conference on Information Systems, AMCIS 2008</i>
5
, pp. 2836-2846
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<div id="previewAbstract95"><span class="txt">The widespread usage of 
the Web and later of the Web 2.0 for social interactions has stimulated 
scholars of different disciplines in studying electronic communities. 
Traditionally, communities are observed as a static phenomenon. However,
 they are evolving constellations, which emerge, lose members and obtain
 new ones and potentially, grow, coerce, split or decline. Such dynamic 
phenomena require the study of social networks across the time axis.We 
propose the graph mining algorithm DENGRAPH for the discovery and 
monitoring of evolving communities. Data mining methods are successfully
 used for community discovery but are mostly limited to the static 
perspective. Taking a dynamic perspective implies the study of a stream 
of interactions among community members. Accordingly, our DENGRAPH is an
 incremental graph mining algorithm, which detects and adapts 
communities over time. We report on our first results in applying 
DENGRAPH on the social network of mail interactions of ENRON.</span></div>
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<i>Academy of Management 2008 Annual Meeting: The Questions We Ask, AOM 2008</i>
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<div id="previewAbstract96"><span class="txt">In this article I 
investigate the role of social network ties as determinants of the 
reputation and identity of individuals. In an extension of research on 
cognitive factors of social network ties, I propose that an individual's
 ego-network composition affects his or her career advancement and 
career resiliency through the mechanisms of reputation and identity. 
Additionally, I focus on individuals affiliated with a common 
institution or focal individual who have come to identify themselves as 
"family members." This form of identification is separate from 
identification with a formal institution and persists through an 
individual's subsequent career positions at different institutions with 
different colleagues. Examples include individuals who worked at 
Fairchild Semiconductor who identified themselves as "Fairchildren" long
 after leaving Fairchild for positions at other organizations (Pollack, 
1988). I utilize a network perspective to investigate recognized 
"family" groups of affiliated coaches in NCAA Division I Men's 
basketball. I propose that coaches affiliated with "coaching families" 
experience greater career opportunity and exhibit greater resiliency due
 to external image benefits and internal identity benefits derived from 
the use of family language. I first analyze all head coaching position 
changes (n=285) between 2001 and 2007 and find that recognition as a 
"family member" is a positive predictor of career advancement. I next 
analyze the subsequent career moves of all coaches that were fired 
(n=155) between 2001 and 2007 and find that "family membership" and 
network connectivity to other active coaches are positive predictors of a
 coach's exhibited career resiliency.</span></div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
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<div id="previewAbstract97"><span class="txt">It is a generally accepted
 idea today that knowledge networks play a crucial role in 
organizations. Knowledge networks refer to knowledge sharing and 
learning as a result of social interactions between employees in an 
organization. Being aware of the importance of these knowledge networks,
 it is of interest to any organization to understand how the performance
 of these networks is influenced by their design. Based on literature we
 defined 7 hypotheses concerning how the structure of knowledge networks
 contributes to the performance of these networks. For testing our 
hypotheses we collected network data from 18 knowledge networks within 
the product line of an international product software company developing
 ERP software. Data was collected by asking employees about their 
learning relations and the frequency of knowledge transfer (independent 
variable). Furthermore, we asked all respondents about the extent to 
which they feel that the knowledge they receive influences their 
perceived job performance, which we converted into a group performance 
measure to measure the performance on network level (dependent 
variable). To test our hypotheses we applied correlation analysis, which
 showed that only part of our hypotheses is supported by the data. We 
found support for a statistically significant relation with group 
performance for efficiency and transitivity, and marginal support for 
density and connectedness. From this we derived preliminary guidelines 
for managers to help them get results from their knowledge networks.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=22941354600&amp;zone=" title="Show author details">Lin, Y.-R.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35561654300&amp;zone=" title="Show author details">Sundaram, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23397254400&amp;zone=" title="Show author details">Kelliher, A.</a>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=55826&amp;origin=resultslist">International Conference on Information and Knowledge Management, Proceedings</a></i>
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<div id="previewAbstract98"><span class="txt">We present a framework for
 automatically summarizing social group activity over time. The problem 
is important in understanding large scale <font class="ScopusTermHighlight">online</font>
 social networks, which have diverse social interactions and exhibit 
temporal dynamics. In this work we construct summarization by extracting
 activity themes. We propose a novel unified temporal multi-graph 
framework for extracting activity themes over time. We use non-negative 
matrix factorization (NMF) approach to derive two interrelated latent 
spaces for users and concepts. Activity themes are extracted from the 
derived latent spaces to construct group activity summary. Experiments 
on real-world Flickr datasets demonstrate that our technique outperforms
 baseline algorithms such as LSI, and is additionally able to extract 
temporally representative activities to construct meaningful group 
activity summary.</span></div>
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2008</div>
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<i>Academy of Management 2008 Annual Meeting: The Questions We Ask, AOM 2008</i>
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<div id="previewAbstract99"><span class="txt">In an effort to deal with 
complex community issues in a more comprehensive and cohesive manner, 
communities have increasingly created locally-based interorganizational 
entities referred to here as community collaboratives. Community 
collaboratives are comprised of representatives from different 
organizations and agencies who meet regularly for the purpose of 
identifying and implementing strategies for improving their 
communityâ€?s response to a specific issue of public concern. This paper
 explores the role of problem frames and perceptions of problem frame 
alignment among members of community collaboratives. Specifically, this 
study uses an innovative combination of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 methods and hierarchical linear modeling to explore how differences in 
the extent to which stakeholders view themselves as in alignment with 
other members and how much they are perceived to be in alignment by 
other members impacts the outcomes of the collaborative as a whole. 
Findings are based off of data from members of 48 different domestic 
violence community collaboratives. Results suggest that the presence of 
stakeholders who are perceived to be philosophically out of sync by 
other stakeholders with regards to their understanding of domestic 
violence but who do not acknowledge this apparent disconnect can 
negatively impact the effectiveness of the collaborative over and above 
the impact associated with the general degree of alignment in the 
collaborative. Implications of results for public and nonprofit 
organizations seeking to provide leadership in promoting the 
effectiveness of community collaboratives are discussed.</span></div>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5376 LNCS
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<div id="previewAbstract100"><span class="txt">The proceedings contain 
25 papers. The topics discussed include: intelligent social network 
modeling and and analysis for security informatics; nature inspired <font class="ScopusTermHighlight">online</font> real risk assessment models for security systems; homeland security data mining using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>;
 the automatic identification and prioritization of criminal networks 
for police crime data; an information theory approach to identify sets 
of key players; locating key actors in social networks using Bayes' 
posterier probability framework; nuclear threat detection via the 
nuclear Web and Dark Web: framework and preliminary study; mapping dark 
Web geolocation; designing information systems which manage to avoid 
privacy incidents; secure computation for privacy preserving biometric 
data retrieval and authentication; and digital audio watermarking for 
copyright protection based on multiwavelet transform.</span></div>
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2008</div>
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Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
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<div id="previewAbstract101"><span class="txt">There have been a number 
of frameworks and models developed to support different aspects of 
social computing. Some were developed to deal with <font class="ScopusTermHighlight">online</font> interaction through the application of computer-mediated communications tools, whereas others such as <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analyses</font>
 and reputation systems were more specific in their focus. While these 
methodologies are inter-related, current social computing research has 
dealt with them as separate aspects. This paper presents a comprehensive
 framework for social computing that aims at integrating all these three
 aspects into a unified model so that discovery and exploration of 
community members are not only made possible, but also optimized. The 
novelty of the proposed approach stems from: (1) integration of social 
interaction, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and social reputation domains; (2) incorporating many flexible and 
practical features such as individual- and group-level perceptions of 
trust in social relations for different social contexts; and (3) using 
path-related algorithms for selection and discovery of target community 
members. A description of the proposed model and its implementation are 
presented. This research is expected to assist <font class="ScopusTermHighlight">online</font>
 community members to make decisions that facilitate the discovery of 
people and their connections while promoting increased awareness of 
community structure and information exposure. © 2008 Springer-Verlag 
Berlin Heidelberg.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5192 LNCS
, pp. 203-215
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<div id="previewAbstract102"><span class="txt">Self-directed Learning 
(SDL) is an old pedagogical concept facing new challenges engendered by 
the emerging social software. We aim to explore the issue how SDL is 
facilitated in <font class="ScopusTermHighlight">online</font> 
cross-cultural collaborative settings - iCamp Trial2 involving faculty 
and students from four European academic institutions. Empirical data of
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 collaborative learning environment empowered by social software could 
potentially enhance that SDL of some but not all the students. The 
actual impact is stipulated by several critical factors such as the 
students' intrinsic motivation and initial anxiety about the learning 
situations. Initial formal structure is essential. Revision of Henri 
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 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5169 LNCS
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<div id="previewAbstract104"><span class="txt">One of the most important
 facets in CSCL research is the interaction between individual and 
collaborative learning activities. This paper proposes a holistic and 
complementary analysis model of the collaborative interactions base on 
three dimensions - process pattern, social relationship and topic space.
 By making use of content analysis, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and text mining technologies, asynchronous discussion transcripts are 
semi-automatically processed to address the questions concerned with 
peer interactions in collaborative learning: what are they talking 
about, who are talking to whom, and how do they talking with others. An 
integrated tool with comprehensive functionalities is designed and 
implemented to support collaborative interaction analysis with 
intelligence and visualization features. With the assistance of the 
tool, a case study is conducted to analyze the discussion records of a 
class composed of 18 graduate students who enrolled in a course along 
with <font class="ScopusTermHighlight">online</font> discussion in knowledge forum platform. © 2008 Springer-Verlag Berlin Heidelberg.</span></div>
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2008</div>
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<div id="previewAbstract105"><span class="txt">Since more and more 
customers get interested in e-commerce, marketing strategy on the 
virtual community becomes a major issue. It is important to help 
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Epinions, a large and popular <font class="ScopusTermHighlight">online</font> product review web site, using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=25632807800&amp;zone=" title="Show author details">Nugroho, Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7801438670&amp;zone=" title="Show author details">Tampubolon, G.</a>
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2008</div>
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<div id="previewAbstract106"><span class="txt">This paper seeks to make 
transparent the mutually reinforcing relationships between global civil 
society, democracy and network society, which are often implicit in 
extant theories. The concept of a 'global civil society' cannot be 
separated from the promotion of democracy. Global civil society itself 
is one of the most explicit instances of the emergence of network 
society in the modern age and democracy lies at the very heart of what 
constitutes a network society. However, very little has been said about 
how these apparent mutually reinforcing relationships arise. Focusing on
 the case of Indonesia during the fraught regime change from 
authoritarianism to democracy, we investigate the role of transnational 
and national civil society organisation during the periods of 
pre-reform, reform and post-reform. Using multi-methods, including <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and interviews with civil society activists and networkers, we discover
 a less encouraging picture of these relationships and conclude that the
 forging of this virtuous circle has some obvious gaps. We attempt to 
account for these apparent gaps in this mutually reinforcing 
relationship in terms of different modes of political participation. We 
suggest that some forms of 'chequebook activism' characterised the 
global civil society role during an abrupt and bloody regime change. © 
Sociological Research <font class="ScopusTermHighlight">Online</font>, 1996-2008.</span></div>
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2008</div>
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<i>IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008</i>
, art. no. 4565020
, pp. 1-6
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<div id="previewAbstract107"><span class="txt">Cyberactivism refers to 
the use of the Internet to advocate vigorous or intentional actions to 
bring about social or political change. Cyberactivism analysis aims to 
improve the understanding of cyber activists and their <font class="ScopusTermHighlight">online</font> communities. In this paper, we present a case study of <font class="ScopusTermHighlight">online</font>
 Free Tibet activities. For web site analysis, we use the inlink and 
outlink information of five selected seed URLs to construct the network 
of Free Tibet web sites. The network shows the close relationships 
between our five seed sites. Centrality measures reveal that tibet.org 
is probably an information hub site in the network. Further content 
analysis tells us that common hub site words are most popular in 
tibet.org whereas dalailama.com focuses mostly on religious words. For 
forum analysis, descriptive statistics such as the number of posts each 
month and the post distribution of forum users illustrate that the two 
large forums FreeTibetAndYou and RFAnews-Tibbs have experienced 
significant reduction in activities in recent years and that a small 
percentage of their users contribute the majority of posts. Important 
phrases of several long threads and active forum users are identified by
 using mutual information and TF-IDF scores. Such topical analyses help 
us understand the topics discussed in the forums and the ideas and 
interest of those forum users. Finally, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analyses</font> of the forum users are conducted to reflect their interactions and the social structure of their <font class="ScopusTermHighlight">online</font> communities. ©2008 IEEE.</span></div>
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<div id="previewAbstract108"><span class="txt">The proceedings contain 67 papers. The topics discussed include: analysis of cyberactivism: a case study of <font class="ScopusTermHighlight">online</font> free Tibet activities; developing ideological networks using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and writeprints: a case study of the International Falun Gong movement;
 detecting deception in testimony; subverting prediction in adversarial 
settings; analyzing content development and visualizing social 
interactions in web forum; link analysis based on webpage co-occurrence 
mining-a case study on a notorious gang leader in Taiwan; a study on 
early decision making in objectionable web content classification; 
information sharing and privacy protection of terrorist or criminal 
social networks; a framework for privacy-preserving cluster analysis; 
WikiNetViz: visualizing friends and adversaries in implicit social 
networks; and constrained K-closest pairs query processing based on 
growing window in crime databases.</span></div>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=15574&amp;origin=resultslist">Information Systems Research</a></i>
19
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<div id="previewAbstract109"><span class="txt">The capabilities offered 
by digital communication are leading to the evolution of new network 
structures that are grounded in communication patterns. As these 
structures are significant for organizations, much research has been 
devoted to understanding network dynamics in ongoing processes of 
electronic communication. A valuable method for this objective is <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>.
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2008</div>
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<div id="previewAbstract110"><span class="txt">The assessment of credibility and reputation of contractors in <font class="ScopusTermHighlight">online</font>
 auctions is the key issue in providing reliable environment for 
customer-to-customer e-commerce. Confident reputation rating system is 
an important factor in managing risk and building customer satisfaction.
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auction sites employ a very simple reputation rating scheme that 
utilizes user feedbacks and comments issued after committed auctions. 
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<div id="previewAbstract111"><span class="txt">An important problem in 
the area of homeland security is to identify abnormal or suspicious 
entities in large data sets. Although there are methods from data mining
 and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 focusing on finding patterns or central nodes from networks or 
numerical data sets, there has been little work aimed at discovering 
abnormal instances in large complex semantic graphs, whose nodes are 
richly connected with many different types of links. In this paper, we 
describe a novel unsupervised framework to identify such instances. 
Besides discovering abnormal instances, we believe that to complete the 
process, a system has to also provide users with understandable 
explanations for its findings. Therefore, in the second part of the 
paper, we describe an explanation mechanism to automatically generate 
human-understandable explanations for the discovered results. To 
evaluate our discovery and explanation systems, we perform experiments 
on several different semantic graphs. The results show that our 
discovery system outperforms state-of-the-art unsupervised network 
algorithms used to analyze the 9/11 terrorist network and other 
graph-based outlier detection algorithms by a significant margin. 
Additionally, the human study we conducted demonstrates that our 
explanation system, which provides natural language explanations for the
 system's findings, allowed human subjects to perform complex data 
analysis In a much more efficient and accurate manner. © 2008 IEEE.</span></div>
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<div id="previewAbstract112"><span class="txt">This paper investigates 
hyperlink patterns in the South Korean political blogosphere. Using 
sampling from the blog sidebar hyperlinks of elected politicians 
(National Assemblymen), the top 79 elite citizen blogs were selected. 
Two data sets were manually compiled during January, 2007: (a) links 
between politicians and citizens, and (b) links amongst citizens. A 
variety of social network analytical methods were then applied. The 
results show that more top blogs have reciprocal links with politicians 
than have unidirectional links. The structure of hyperlink 
interconnectivity suggests that the ruling Uri party affiliated blogs 
are key in the blog network. For example, the blogs tied with the Uri 
party have a higher centrality and are more densely connected. Network 
diagrams also suggest that the top blogs are polarized by party. 
However, some blogs are located at the center of the Uri and GNP 
clusters and are connected to both camps. In other words, there are a 
number of citizen blogs that link to both the Uri and GNP members, 
because their political identities are not completely shaped but also 
remain between 2 different ideologies. This suggests that binary 
opposition in <font class="ScopusTermHighlight">online</font> political discourse is slowly changing. © 2008 International Communication Association.</span></div>
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2008</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
5009 LNAI
, pp. 668-675
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<div id="previewAbstract113"><span class="txt">With the popularity of Web 2.0 websites, <font class="ScopusTermHighlight">online</font>
 social networking has thriven rapidly over the last few years. Lots of 
research attention have been attracted to the large-scale social network
 extraction and analysis. However, these studies are mostly beneficial 
to sociologists and researchers in the area of social community studies,
 but rarely useful to individual users. In this paper, we present a 
"friends ranking" system - visoLink which is a personal <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 service based on user's reading and writing interest. In order to 
provide a better understanding to user's personal network, a weighted 
personal social representation and visualization are proposed. Our 
system prototype shows a much more user friendly design on personal 
networks than the classical node-edge distance based network 
visualization. © 2008 Springer-Verlag Berlin Heidelberg.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24491230200&amp;zone=" title="Show author details">Vergeer, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24490710300&amp;zone=" title="Show author details">Hermans, L.</a>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=27635&amp;origin=resultslist">Javnost</a></i>
15
(2)
, pp. 37-56
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<div id="previewAbstract114"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 political discussions are thought to lead to more political engagement 
and empowerment of peripheral groups in society and thereby contributing
 to deliberative citizenship. Because people have increased 
opportunities to voice their political opinions and publish these for a 
potentially large audience to read, the involved level of interactivity 
can mobilise people who would otherwise not have been in political life.
 Since Web 2.0 applications (i.e. blogs, social networking sites) have 
become popular, <font class="ScopusTermHighlight">online</font> discussions have taken a great flight on the web. This article discusses the advantages and difficulties of studying <font class="ScopusTermHighlight">online</font> discussions applying a mixed method approach of content analysis, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and longitudinal analysis. The additional value of using a combination 
of research methods simultaneously is that it does justice to the 
complex object of study because a more in-depth and triangulated 
measurement of political communications can be established. The 
methodological implications will be illustrated on data from the <font class="ScopusTermHighlight">online</font> political discussion group, nl.politiek, one of the most active discussion groups during the Dutch national elections in 2006.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15520999600&amp;zone=" title="Show author details">Markauskaite, L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16232069500&amp;zone=" title="Show author details">Sutherland, L.M.</a>
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7
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<div id="previewAbstract115"><span class="txt">An exploratory study of students' engagement in <font class="ScopusTermHighlight">online</font> learning and knowledge building is presented in this paper. Learning in an <font class="ScopusTermHighlight">online</font>
 community, composed of students (pre-service teachers) and experts 
(experienced in-service schoolteachers and academics), is the study's 
primary focus. Students' interaction and knowledge discourse structures,
 arising from individual readings of academic papers and asynchronous 
collaboration with peers and experts, are investigated using social 
network and content analysis techniques. Additionally, several new 
measures for exploring structural-qualitative aspects of knowledge 
discourse are introduced. Analysis revealed several important trends. 
First, students' interaction was more intensive in forums where 
experienced teachers participated, rather than students only. Second, 
students' individual discourse structures in their postings were quite 
deep, knowledge-focussed and elaborated; while students' replies were 
short, usually focussed on specific idea and contained a substantial 
amount of non-cognitive information. Overall, it is argued that students
 were engaged with the individual and collaborative knowledge building 
in the <font class="ScopusTermHighlight">online</font> teaming 
community. Practical implications of the study results for development 
of courses are discussed. © 2008 Institute of Mathematics and 
Informatics, Vilnius.</span></div>
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2008</div>
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18
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<div id="previewAbstract116"><span class="txt">Purpose - To evaluate and extend, existing natural language processing techniques into the domain of informal <font class="ScopusTermHighlight">online</font>
 political discussions. Design/methodology/approach - A database of 
postings from a US political discussion site was collected, along with 
self-reported political orientation data for the users. A variety of 
sentiment analysis, text classification, and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 methods were applied to the postings and evaluated against the users' 
self-descriptions. Findings - Purely text-based methods performed 
poorly, but could be improved using techniques which took into account 
the users' position in the <font class="ScopusTermHighlight">online</font>
 community. Research limitations/implications - The techniques we 
applied here are fairly simple, and more sophisticated learning 
algorithms may yield better results for text-based classification. 
Practical implications - This work suggests that <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 is an important tool for performing natural language processing tasks 
with informal web texts. Originality/value - This research extends 
sentiment analysis to a new subject domain (US politics) and a new text 
genre (informal <font class="ScopusTermHighlight">online</font> discusssions). © Emerald Group Publishing Limited.</span></div>
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2008</div>
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<div id="previewAbstract117"><span class="txt">The reputation system 
currently used by major auction sites to recommend sellers is overly 
simple and fails to take into account the collusive attempts by some 
sellers to fraudulently increase their own ratings. This paper presents a
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level of recommendation for trusted <font class="ScopusTermHighlight">online</font>
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recommendation system that could suggest risks of collusion associated 
with an account. We tested this system against real world "blacklist" 
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warning several months ahead of officially released blacklists to help 
guard against possible seller collusion and can be incorporated into 
current reputation systems used to recommend trusted <font class="ScopusTermHighlight">online</font> auction sellers. © 2007 Elsevier Ltd. All rights reserved.</span></div>
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2008</div>
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<div id="previewAbstract118"><span class="txt">This article explores the
 social network of learning beyond a functional understanding of social 
relations. It describes and interprets the realities of networked 
learning within a particular postgraduate course in an English 
university setting. It draws attention to some of the limitations of the
 increasing interest in the use of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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relational effects of multiple technical and social arrangements and 
engagements beyond the response relations the <font class="ScopusTermHighlight">online</font>
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network processes rather than network structures. © 2007 Blackwell 
Publishing Ltd.</span></div>
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<div id="previewAbstract119"><span class="txt">This paper contributes to
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<i>ACM International Conference Proceeding Series</i>
258
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<div id="previewAbstract121"><span class="txt">Purchasing decisions are often strongly influenced by people who the consumer knows and trusts. Moreover, many <font class="ScopusTermHighlight">online</font>
 shoppers tend to wait for the opinions of early adopters before making a
 purchase decision to reduce the risk of buying a new product. Web-based
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consumers to share their personal experiences by writing reviews, rating
 reviews, and chatting among trusting members. They drive the volume of 
traffic to retail sites and become a starting point for Web shoppers. 
E-commerce companies have recently started to capture data on the social
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objective of understanding and leveraging social influence in customers'
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and increase sales. In this paper, we present an overview of the impact 
of social influence in E-commerce decision making to provide guidance to
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identify how data about social influence can be captured from <font class="ScopusTermHighlight">online</font>
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websites to aid the user decision making process. We also provide a 
summary of technology for <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and identify the research challenges of measuring and leveraging the 
impact of social influence on E-commerce decision making. Copyright 2007
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8
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<div id="previewAbstract122"><span class="txt">In this exploratory 
study, Cocciolo, Chae and Natriello investigate the extent to which the 
communicative processes exhibited within a large digital repository 
illustrate the emergence of an <font class="ScopusTermHighlight">online</font> community of practice (CoP). In order to make this claim, we present a method for identifying the emergence of an <font class="ScopusTermHighlight">online</font> CoP using <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA) on communication data (i.e., uploads and downloads) and 
institutional role (i.e., expert/faculty vs. novice/student). The 
analysis reveals that the <font class="ScopusTermHighlight">online</font>
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2007</div>
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<div id="previewAbstract123"><span class="txt">This paper contributes to the growing body of knowledge which identifies benefits for <font class="ScopusTermHighlight">online</font>
 learning in the understanding of mediated social processes. It reports 
on an exploratory study into the nature, role and function of <font class="ScopusTermHighlight">online</font> social presence and a potential link between social presence and learner support in text-based <font class="ScopusTermHighlight">online</font>
 learning environments. Employing a qualitative collective case study 
design, the study sought to produce understandings of mediated social 
processes which were grounded in the experiences of learners in 
text-based <font class="ScopusTermHighlight">online</font> learning environments. Informed by <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>, the paper presents key findings of that study including (a) a definition of social presence as described by <font class="ScopusTermHighlight">online</font> learners (b) the role social presence in the development of relations and ties between <font class="ScopusTermHighlight">online</font>
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2007</div>
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<i>GROUP'07 - Proceedings of the 2007 International ACM Conference on Supporting Group Work</i>
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<div id="previewAbstract124"><span class="txt">The rise of social software poses the challenges to the design and evaluation of a pedagogically sound <font class="ScopusTermHighlight">online</font>
 learning environment (OLE). Our OLE addresses these challenges by the 
integration of three pedagogical concepts - cross-cultural 
collaboration, self-directed learning and social networking - with the 
aim to advance participants' competencies and by mixed-method approaches
 to evaluating the complex situations. A validation trial involving four
 European countries was conducted. Groups of students co-created a 
questionnaire, which was assessed to provide an indicator of task 
performance. Multi-source (surveys, blogs, emails, diaries, chats, 
videoconference, and interviews) and multi-perspective data 
(facilitators, students, researchers) were studied with <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>, content analysis and conversation analysis. Several a posteriori research questions are addressed. © 2007 ACM.</span></div>
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2007</div>
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<i>2007 International Conference on Convergence Information Technology, ICCIT 2007</i>
, art. no. 4420579
, pp. 2193-2198
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<div id="previewAbstract125"><span class="txt">We use blogs as tools of 
social learning. By browsing the selected peer works and the comments 
made by peers as well as instructors on students' blogs, students are 
empowered to stimulate new ideas different from each other. Survey 
results show that students who took the lab courses are satisfied with 
turning in lab results through blog posting, getting instructor's 
in-class interactions, piracy reduction, and social learning. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 further indicates the degree of the social connectedness in the 
learning group is high. With probability 65.8%, namely nearly 2 out 3, 
the 36 participants by making only 3.5 comments per person in average, 
can chase the dialogue links and read their peers' works along in just a
 few chained links (all below 7, and 2.8 on average in our case). We 
also found there existed a few opinion leaders, 4 out of 36, in the 
group. Those opinion leaders created opportunities for their peers to 
expose themselves to high quality works which served as live model 
examples. © 2007 IEEE.</span></div>
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feedback and the incorrect feedback were not accompanied by any 
significant modification. © Springer-Verlag Berlin Heidelberg 2007.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=51462314000&amp;zone=" title="Show author details">Wu, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55501795400&amp;zone=" title="Show author details">Goh, K.Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55501901600&amp;zone=" title="Show author details">Tang, Q.</a>
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2007</div>
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<i>ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems</i>
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<div id="previewAbstract130"><span class="txt">To date, numerous open source projects are hosted on many <font class="ScopusTermHighlight">online</font>
 repositories, reflecting the popularity of open source projects. While 
some of these projects are active and thriving, some of them are either 
languishing or showing no development activities at all. This phenomenon
 thus begs the important question of what are the influential factors 
that affect the success of open source projects. In a quest to deepen 
our understanding of the evolution of open source projects, this 
research aims to analyze the survival of open source projects by using 
the theoretical lens of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>. Based on extensive analyses of empirical data collected from <font class="ScopusTermHighlight">online</font>
 open source repositories, we study the impact of the communication 
patterns of the development teams on the outcomes of these projects, 
while accounting for project-specific characteristics. Using panel data 
analysis, we find significant impacts of communication patterns on 
project outcomes over the long term.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7404908149&amp;zone=" title="Show author details">Chen, F.-C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55099192300&amp;zone=" title="Show author details">Jiang, H.-M.</a>
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2007</div>
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<i>Computer-Supported Collaborative Learning Conference, CSCL</i>
8
(PART 1)
, pp. 128-131
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0
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<div id="previewAbstract131"><span class="txt">Little research has been 
conducted on human support in CSCL situations. Extensive investigations 
on human meta-support are, in fact, rare. In this study, we have 
developed a set of mechanisms to facilitate human meta-support in a CSCL
 environment. Thirteen cognitive-affective pairs of mentors who 
facilitate a total of 82 forum groups share and discuss their mentoring 
practice in an exclusive Mentoring Forum. Using <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>,
 we have explored the dynamics within and among pairs of mentors to 
reveal how they engaged in this environment and how they coconstructed 
their knowledge on how best to support a group of learners.</span></div>
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1132
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<a href="http://www.scopus.com/record/display.url?eid=2-s2.0-84870970586&amp;origin=resultslist&amp;sort=plf-f&amp;src=s&amp;st1=%22social+network+analysis%22+AND+online&amp;nlo=&amp;nlr=&amp;nls=&amp;sid=F24707DC9D3767AFFD5F36FE052141BF.CnvicAmOODVwpVrjSeqQ%3a20&amp;sot=b&amp;sdt=b&amp;sl=51&amp;s=TITLE-ABS-KEY%28%22social+network+analysis%22+AND+online%29&amp;relpos=1131&amp;relpos=131&amp;searchTerm=TITLE-ABS-KEY%28%5C%26quot%3Bsocial+network+analysis%5C%26quot%3B+AND+online%29" onclick="javascript:submitRecord('2-s2.0-84870970586','131','0');">Social network analysis and organizational disintegration: The case of enron corporation</a>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55501975900&amp;zone=" title="Show author details">Hasan Murshed, S.T.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7405963529&amp;zone=" title="Show author details">Davis, J.G.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=18634019100&amp;zone=" title="Show author details">Hossain, L.</a>
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2007</div>
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<i>ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems</i>
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0
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<div id="previewAbstract132"><span class="txt">Email networks in 
contemporary organizations are fairly representative of the underlying 
communications networks. We show that changes in communication networks 
have implications for studying organization disintegration. In this 
paper, we analyzed the changing communication network structure at Enron
 Corporation during the period of its disintegration (2000-2001). Our 
goal was to understand how communication patterns and structure were 
affected by organizational disintegration. Drawing on (social) network 
disintegration theory, we tested several propositions using the Enron 
email corpus: (1) Number of cliques increases (2) Communication network 
becomes increasingly centralized, and (3) Connectedness among the top 
management executives increases, as organizations move towards 
disintegration. The results of the tests and their implications are 
discussed.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602832111&amp;zone=" title="Show author details">Harrer, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8961496400&amp;zone=" title="Show author details">Malzahn, N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8961496200&amp;zone=" title="Show author details">Zeini, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=34769829400&amp;zone=" title="Show author details">Hoppe, H.U.</a>
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2007</div>
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<i>Computer-Supported Collaborative Learning Conference, CSCL</i>
8
(PART 1)
, pp. 267-276
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<div id="previewAbstract133"><span class="txt">This paper presents an 
analytical approach to support organisational learning in terms of the 
evolution of a scientific community based on a combination of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and semantic relations. The primary and direct target of the method is 
to infer hidden or desirable links between subgroups in a networked 
community. The data source for these inferences comprises memberships in
 teams and thematic subgroups. The approach has been applied in a case 
study to a large scientific network on technology enhanced learning.</span></div>
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2007</div>
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<i>IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management</i>
, art. no. 4419181
, pp. 209-213
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<div id="previewAbstract134"><span class="txt">The study presents the analysis of Collaborative Product Commerce documents associated by using co-citation analysis and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 Co-citation is a new form of document coupling the frequency with which
 two documents are cited together. In this paper we report an experiment
 by using data from Google scholar search and Social Science Citation 
Index to identify clusters of highly interactive documents in the 
subject of Collaborative Product Commerce. They may provide a new 
approach to indexing and to the creation easier search CPC area. The 
study discovers five core papers which imply the four documents provide 
insight into the theory's evolution and clarifies future research work 
in CPC field. The trend in the field focuses on organizational layer, 
included knowledge management, system problem solution, and 
collaborative mechanism design. The conclusion can provide future 
research direction for the researcher in this field. © 2007 IEEE.</span></div>
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2007</div>
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<i>GROUP'07 - Proceedings of the 2007 International ACM Conference on Supporting Group Work</i>
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<div id="previewAbstract135"><span class="txt">Employees depend on other
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 current systems for finding experts do not adequately address the 
social implications of finding and engaging strangers in conversation. 
This paper provides a user study of SmallBlue, a social-context-aware 
expertise search system that can be used to identify experts, see 
dynamic profile information and get information about the social 
distance to the expert, before deciding whether and how to initiate 
contact. The system uses an innovative approach to privacy to infer 
content and dynamic social networks from email and chat logs. We 
describe usage of SmallBlue and discuss implications for the next 
generation of enterprise-wide systems for finding people. © 2007 ACM.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=23643&amp;origin=resultslist">Health Informatics Journal</a></i>
13
(4)
, pp. 255-266
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<div id="previewAbstract136"><span class="txt">Knowledge is a critical 
element in the delivery of quality healthcare. In a busy emergency 
department (ED) clinicians attempting clinically relevant discussion 
with their peers face multiple interruptions and a lack of sustained 
meaningful interactions. Information and communication technologies such
 as <font class="ScopusTermHighlight">online</font> discussion forums 
enable practitioners to share practice knowledge at times that fit into 
their daily workflow. We conducted an experiment in which we provided 
emergency clinicians with access to an asynchronous discussion forum as a
 medium to support development of an <font class="ScopusTermHighlight">online</font>
 social network for information exchange. The outcomes were evaluated 
using a social network perspective to better understand the knowledge 
seeking and sharing behaviors among rural and urban emergency 
practitioners participating in the <font class="ScopusTermHighlight">online</font> discussion forum. The <font class="ScopusTermHighlight">online</font>
 discussion forum created an opportunity for emergency practitioners 
from multiple ED sites to engage in dialogue around topics that were 
relevant to their practice learning needs. © SAGE Publications, 
Inc.2007.</span></div>
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2007</div>
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<i>Computer-Supported Collaborative Learning Conference, CSCL</i>
8
(PART 2)
, pp. 865-867
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<div id="previewAbstract137"><span class="txt">As <font class="ScopusTermHighlight">online</font> tools and social web sites become more popular, people are sharing more of their creations <font class="ScopusTermHighlight">online</font>. This thesis uses <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 to understand how community members share creations and learn from one 
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diffuse through them, which ideas are adopted and incorporated into 
members' work, and how members describe the ways their work relates to 
others'.</span></div>
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<i>ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems</i>
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0
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<div id="previewAbstract138"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 policy discussion forums can be construed as a social network where 
citizens interact and collectively deliberate on policy issues. It is 
believed that citizen participation in such forums can help in the 
formulation of well-deliberated policy solutions. A key concern for 
governments is to promote participation in such forums. Social network 
literature reveals that the evolving interaction patterns between 
network participants can influence their collective behaviors. Thus, 
this study aims to investigate the longitudinal effects of network 
structural properties on forum participation using time series analysis.
 Our findings reveal that network structure can have both positive and 
negative effects on participation in terms of the number of postings and
 unique ideas contributed. This theoretically grounded empirical study 
on e-participation, employing ARIMA modeling with transfer function 
analysis on social network measures, contributes to the diversity of 
theories and methods in IS research. Implications for practice are also 
discussed.</span></div>
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2007</div>
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<i>Proceedings ISM Workshops 2007 9th IEEE International Symposium on Multimedia - Workshops</i>
, art. no. 4476009
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activities. Particular attention is paid to measures of sense of 
community and social ability. A multiple data analyses, including 
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patterns found in SNA. © 2007 IEEE.</span></div>
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<i>Proceedings of the 2007 International Symposium on Collaborative Technologies and Systems, CTS</i>
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<div id="previewAbstract140"><span class="txt">This paper introduces a 
new way of measuring the popularity of brand names and famous people 
such as movie stars, politicians, and business executives. It is based 
upon the premise that in today's Internet economy the Web displaysa 
mirrorof the realworld. Our system uses TeCFlow, a social networking 
tool developed for the last four years at MIT, to measure popularity and
 influenceof brandsand stars by lookingat theirrelative position on the 
Web. It is based on the simple insight: "You are who links to you ". It 
applies the <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>(SNA)metricof
 "betweennes scentrality "to the Web, lookingat the linkingstructureof 
Web sites to find how Web pages discussing brands and stars are 
connected. It uses high-betweennessWeb sites returned to a search engine
 query for a brand or star name as a proxy for the significance of this 
brand or star. © 2007 IEEE.</span></div>
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<i>ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems</i>
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<div id="previewAbstract141"><span class="txt">This paper applies <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 techniques to study computer virus propagation. We propose a novel 
multilevel hierarchical linear model to simultaneously evaluate the 
impact of both individual-level and group-level variables on virus 
propagation process. In this model, we propose centrality and brokerage 
measures as explanatory variables. We estimate our model based on 
empirical data from the largest social networking website and find that 
closeness centrality (individual level) and brokerage (group level) 
jointly explain 82.5% of the variance in the number of infections. This 
research contributes to both the literature of computer virus 
propagation and defense and the literature of centrality measure 
comparison in the filed of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 by: (1) performing subgroup analysis and considering multiple levels of
 network characteristics to capture the intrinsic nested feature of the 
networks and (2) comparing different structural measures (centrality and
 brokerage) in terms of their performance to explain the propagation of 
computer viruses.</span></div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 696-702
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<div id="previewAbstract142"><span class="txt">Effective and efficient 
knowledge creation, sharing and application are indispensable in 
nowadays globalised and knowledge-based economy. To maintain 
competitiveness especially knowledge-intensive organisations have to 
establish a working environment that supports the entire chain of 
knowledge processing. arsenal research, an applied research 
organisation, has therefore decided to support Communities of Practice 
to improve knowledge transfer and application. The communities mainly 
focus on the cultivation of a collaborative and innovative working 
environment that cross-links its multidisciplinary research staff. To 
allow for an objective evaluation of the communities and the achieved 
improvements <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 is applied. Main objective of this analysis is to identify the 
communication behaviour and knowledge transfer especially across the 
different business units. As a reference for the evaluation process a 
network analysis has been performed at the beginning of the communities'
 development phase. Network analysis has emerged as a set of methods for
 the analysis of (social) structures by focusing on investigation of the
 relational aspects of these structures. Network analysis combined with 
visualisation is a very useful tool for supporting the analysis. Few 
core indicators of <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 have been applied for calculating the community networks. A directed 
graph of a one node network visualized via PAJEK has been applied. 
Different aspects of the communication and collaboration behaviour have 
been analysed with this method. The results of this basic analysis give 
some insights into the communication behaviour of the scientists at the 
starting phase of the communities. The results clearly indicate what has
 also been experienced in the development process-a lack of 
communication and cross-linking between the different organisational 
units. The paper gives an overview over the applied method for network 
analysis, a discussion of the results in the context of the experiences 
made in the first phase of the communities as well as an outlook 
regarding the further steps.</span></div>
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2007</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=19700186824&amp;origin=resultslist">Journal of Software</a></i>
2
(6)
, pp. 22-29
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<div id="previewAbstract143"><span class="txt"><font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 has been used for quite some time to analyze and understand the 
behavior of nodes in the network. Theses nodes could be individuals or 
group of persons, events or organizations etc. Infact these nodes could 
be any thing importantly, these nodes propagate and obviously have 
attributes. In this paper a very novel and absolutely new approach to 
SNA is presented, for locating the important key players in the network.
 The system also predicts a path comprising of selected nodes which 
shows the vulnerability of the network and if the path along with these 
nodes is removed it can reduce/destabilize or even destroy the structure
 of the network. The paper provides comparative results for a couple of 
random networks with various numbers of nodes and connections. In 
addition to these example networks it performs a case study of the nine 
eleven, 62 node networks (by Valdis E. Krebs) to predict a path for its 
destabilization. This network is selected to benchmark our proposed 
model framework. The results obtained with various network analysis 
shows that it works better than other analysis measures for example 
based on degree, betweeness and closeness etc. © 2006 ACADEMY PUBLISHER.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23392932300&amp;zone=" title="Show author details">Ku, Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402303950&amp;zone=" title="Show author details">Chiu, C.</a>
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2007</div>
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<i>Proceedings of the International Conference on Electronic Business (ICEB)</i>
, pp. 68-73
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0
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<div id="previewAbstract144"><span class="txt">People often enmesh the 
Internet auction frauds which damage the benefits of Internet market and
 threaten transactions security. This research applies <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and data mining to extract characteristic features from two random 
collected transaction datasets of Yahoo auction site. One dataset is 
used to construct prediction model and another is treated as validation.
 The average accuracy ratio of proposed model is at least 90%. The 
findings are: (1) the abnormal accounts involve circular transaction; 
(2) fraud accounts can accumulate higher positive reputations in very 
short time from its circular transaction and rarely play key nodes in 
transaction network.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=42862443000&amp;zone=" title="Show author details">Wagner-Luptacik, P.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=11440526100&amp;zone=" title="Show author details">Hörlesberger, M.</a>
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2007</div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 1093-1099
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<div id="previewAbstract145"><span class="txt">Knowledge networks are 
thus the critical knowledge infrastructure of Communities of 
Practice(CoP). Knowledge sharing is a core process in knowledge 
management. This is particularly the case for research organizations 
where due to the heterogeneous nature of scientific communities in 
applied research, building researcher's knowledge and expertise is not 
restricted to a single scientific community. Expert learning involves 
participating in different communities and switching the role of novice 
and expert is context-specific. A community of research practice (CoRP) 
contributes towards more effective and efficient knowledge production 
and experience sharing between researchers. This will be empirically 
illustrated through the case of an applied research organization 
wherecommunities of practice were initiated by management in order boost
 research performance. Based onasurvey of information and advice 
networks we will use <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 to visualize the structural characteristics of knowledge networks 
within a CoRP (network-centric view). We then investigate the position 
of individual researchers in the network as this influences 
communication patterns (person-centric view). There are different 
knowledge functions associated with different positions a member has in 
the network and corresponding network metrics: authority (high in-degree
 centrality), hub (high out-degree centrality), and brokers (high 
betweenness and/or closeness centrality) are key roles in knowledge 
transfer. Qualitative information based on expert interviews willprovide
 implications for further monitoring the progress in CoRP development 
into systematic value-creating networks.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6507877152&amp;zone=" title="Show author details">Casciaro, T.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7006647492&amp;zone=" title="Show author details">Lobo, M.S.</a>
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2007</div>
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<i>Academy of Management 2007 Annual Meeting: Doing Well by Doing Good, AOM 2007</i>
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<div id="previewAbstract146"><span class="txt">This paper examines the 
role of interpersonal affect in networks of instrumental action in 
organizations. We aim to answer two related questions. First, does 
interpersonal affect modify the use of task competence as a criterion 
for the formation of instrumental ties? Second, does negative affect 
influence the role of task competence in instrumental relationships 
differently than positive affect? Based on a methodology drawing from 
social psychological models of interpersonal perception and hierarchical
 Bayesian models for <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 we investigated these questions with data from three network studies of
 an entrepreneurial computer technology company, staff personnel at an 
academic institution, and employees in a large information technology 
corporation. Across all the organizational contexts and tasks we 
analyzed, we found that, in the presence of negative affect, competence 
was largely irrelevant as a criterion for the formation of instrumental 
ties. By contrast, under conditions of positive affect, increases in 
task competence had a consistently positive effect on the likelihood of 
work interaction. We conclude that, by changing how people seek out and 
access the competence of their colleagues, the structure of 
interpersonal affect has pervasive consequences for the functioning of 
organizations.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=27067456500&amp;zone=" title="Show author details">Berger, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7401522730&amp;zone=" title="Show author details">Peters, G.</a>
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2007</div>
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<i>ICEIS 2007 - 9th International Conference on Enterprise Information Systems, Proceedings</i>
SAIC
, pp. 235-240
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0
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<div id="previewAbstract147"><span class="txt">There is ongoing 
discussion whether and to which extent and aspects professionals in the 
field of information technology (IT) and business administration (BA) 
are different. Often IT people are considered to be introverted while it
 is assumed that BA professionals are stronger with respect to 
communication and networking. In our paper we take a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> perspective to examine if this prejudice is true for BA and IT professionals who are members of an <font class="ScopusTermHighlight">online</font> business community.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24474098300&amp;zone=" title="Show author details">Forsyth, E.N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15756003300&amp;zone=" title="Show author details">Martell, C.H.</a>
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2007</div>
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<i>ICSC 2007 International Conference on Semantic Computing</i>
, art. no. 4338328
, pp. 19-26
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<div id="previewAbstract148"><span class="txt">One of the ultimate goals
 of natural language processing (NLP) systems is understanding the 
meaning of what is being transmitted, irrespective of the medium (e.g., 
written versus spoken) or the form (e.g., static documents versus 
dynamic dialogues). Although much work has been done in traditional 
language domains such as speech and static written text, little has yet 
been done in the newer communication domains enabled by the Internet, 
e.g., <font class="ScopusTermHighlight">online</font> chat and instant 
messaging. This is in part due to the fact that there are no annotated 
chat corpora available to the broader research community. The purpose of
 this research is to build a chat corpus, tagged with lexical (token 
part-of-speech labels), syntactic (post parse tree), and discourse (post
 classification) information. Such a corpus can then be used to develop 
more complex, statistical-based NLP applications that perform tasks such
 as author profiling, entity identification, and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=52763817400&amp;zone=" title="Show author details">Wang, W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=9337843600&amp;zone=" title="Show author details">Barnaghi, P.M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7004250697&amp;zone=" title="Show author details">Bargiela, A.</a>
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2007</div>
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<i>Proceedings - ALPIT 2007 6th International Conference on Advanced Language Processing and Web Information Technology</i>
, art. no. 4460643
, pp. 218-223
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<div id="previewAbstract149"><span class="txt">Information Retrieval 
(IR) techniques have been extensively studied since late 1940s and 
achieved great success evidenced particularly by popular <font class="ScopusTermHighlight">online</font>
 search engines. However, various classical information retrieval models
 also have witnessed criticism for emphasizing computation with 
occurrence of words while ignoring semantics (i.e. meaning of words, 
search context and etc). Research of the Semantic Web in recent years 
has provided an opportunity to migrate from mere word-computing to 
semantic-enhanced information search and retrieval. In this paper, we 
describe a methodology by combing the Semantic Web technologies, 
information extraction and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 techniques to elicit semantics from available data in order to develop a
 semantic-enhanced information search and retrieval system. © 2007 IEEE.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=23974111400&amp;zone=" title="Show author details">Ellis, T.S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402530404&amp;zone=" title="Show author details">Yao, X.</a>
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2007</div>
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<i>2007 IEEE Congress on Evolutionary Computation, CEC 2007</i>
, art. no. 4424544
, pp. 736-743
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<div id="previewAbstract150"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 service provision is becoming increasingly decentralized as system 
designers pursue the benefits gained from utilizing nodes at the 
periphery of the network. However, distributing control means relying on
 the cooperation of participating agents, and it is a significant 
challenge to design mechanisms that incentivise optimal global behavior 
in a population of selfish, rational agents. This is particularly 
evident in peer-to-peer file-sharing, where a high incidence of selfish 
behavior in the form of downloading without uploading, leads to the 
network losing the benefits of a decentralized network. In this paper a 
notion of reputation based on simple <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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strategy would be for all agents to defect. © 2007 IEEE.</span></div>
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<i>NAACL HLT 2007 - Human Language Technologies 2007: The Conference of 
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Linguistics, Proceedings of the Main Conference</i>
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<div id="previewAbstract151"><span class="txt">We introduce a novel 
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 on diversity. That is, the top items should be different from each 
other in order to have a broad coverage of the whole item set. Many 
natural language processing tasks can benefit from such diversity 
ranking. Our algorithm is based on random walks in an absorbing Markov 
chain. We turn ranked items into absorbing states, which effectively 
prevents redundant items from receiving a high rank. We demonstrate 
GRASSHOPPER's effectiveness on extractive text summarization: our 
algorithm ranks between the 1st and 2nd systems on DUC 2004 Task 2; and 
on a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> task that identifies movie stars of the world. © 2007 Association for Computational Linguistics.</span></div>
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2007</div>
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<i>Conferences in Research and Practice in Information Technology Series</i>
70
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<div id="previewAbstract152"><span class="txt">Since discovery of an 
underlying organisational structure from crime data leads the 
investigation to terrorist cells or organised crime groups, detecting 
covert networks are important to crime investigation. As shown in 
application of Offender Group Detection Model (OGDM), which is developed
 and tested on a theft network in Bursa, Turkey, use of effective data 
mining methods can reveal offender groups. OGDM detected seven ruling 
members of twenty network members. Based on initial findings of OGDM; 
thirty-four offenders are considered to be in a single offender group 
where seven of them were ruling members. After Operation Cash was 
launched, the police arrested the seven detected ruling members, and 
confirmed that the real crime network was consisting of 20 members of 
which 3 whom had never been previously identified or arrested. The 
police arrested 17 people, recovered worth U.S. $ 200,000 of stolen 
goods, and cash worth U.S. $ 180,000. © 2007, Australian Computer 
Society, Inc.</span></div>
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<i>Computer-Supported Collaborative Learning Conference, CSCL</i>
8
(PART 1)
, pp. 428-437
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<div id="previewAbstract153"><span class="txt">Interaction analysis 
plays an important role in computer-supported collaborative learning. 
This paper proposes a multidimensional analysis framework to study the 
interaction and makes use of the quantitative analysis method to assess 
the collaborative knowledge building (CKB) outcomes at individual and 
group levels. A tool is developed that can support interaction analysis,
 text analysis, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 and a combination of the above to show the differences of cognitive 
content and constructive level in terms of collaborative knowledge 
building. A case study of the interaction analysis via using the tool is
 presented.</span></div>
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 network position, industry hierarchy position and innovation and an 
additional examination on structural equivalent block models and 
between-sector position</a>
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<i>Academy of Management 2007 Annual Meeting: Doing Well by Doing Good, AOM 2007</i>
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<div id="previewAbstract154"><span class="txt">In contrast to the focus on the social ties of individual actor in the conventional <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 in this research, we explore how a firmis industrial network position 
and industry hierarchy position based on its institutional ties 
influences its technological innovation. I n this research we find that 
firms with a good network position will result in more innovation and 
its industry hierarchy position will moderate the above relationships. 
We also make investigations on block models based on structural 
equivalence, general network advantages based on combination of network 
position and industry hierarchy position, and between-sector position 
comparison to the firms within the same value chain sector. By these 
investigations we find that blocks with more connection to other blocks 
will result in more innovation in the blocks, firms with different 
general network position advantages will perform differently in 
innovation, and firms with more between-sector connections will perform 
better in innovation comparing to the other firms in the same sector. 
Research limitation and future direction are also discussed and provided
 in this research.</span></div>
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2007</div>
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<i>LWA 2007 - Lernen - Wissen - Adaptivitat - Learning, Knowledge, and Adaptivity, Workshop Proceedings</i>
, pp. 330-337
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<div id="previewAbstract155"><span class="txt">Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular <font class="ScopusTermHighlight">online</font> communities for creating, editing and sharing content. However, the rapid increase in size of <font class="ScopusTermHighlight">online</font>
 communities and the availability of large amounts of shared data make 
discovering relevant content and finding related users a difficult task.
 Web 2.0 applications provide a rich set of structures and annotations 
that can be mined for a variety of purposes. In this paper we propose a 
formal model to characterize users, items, and annotations in Web 2.0 
environments. Based on this model we propose recommendation mechanisms 
using methods from <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
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construct collaborative recommender systems that predict the utility of 
items, users or groups based on the multi-dimensional social environment
 of a given user.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8961496400&amp;zone=" title="Show author details">Malzahn, N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602832111&amp;zone=" title="Show author details">Harrer, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8961496200&amp;zone=" title="Show author details">Zeini, S.</a>
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2007</div>
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<i>Computer-Supported Collaborative Learning Conference, CSCL</i>
8
(PART 2)
, pp. 547-550
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<div id="previewAbstract156"><span class="txt">In this paper we propose an approach based on <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 facilitated by ontologies for the support of learning group formation 
in computer supported collaborative and blended learning scenarios. This
 approach allows us to generate new ties between learners who are 
interested in similar topics. The identification of similar topics is 
elaborated dynamically by using a shared workspace environment which 
supports visual editing and modeling of topic relationships.</span></div>
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<i>16th International World Wide Web Conference, WWW2007</i>
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<div id="previewAbstract157"><span class="txt">Web-based communities 
have become important places for people to seek and share expertise. We 
find that networks in these communities typically differ in their 
topology from other <font class="ScopusTermHighlight">online</font> 
networks such as the World Wide Web. Systems targeted to augment 
web-based communities by automatically identifying users with expertise,
 for example, need to adapt to the underlying interaction dynamics. In 
this study, we analyze the Java Forum, a large <font class="ScopusTermHighlight">online</font> help-seeking community, using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 methods. We test a set of network-based ranking algorithms, including 
PageRank and HITS, on this large size social network in order to 
identify users with high expertise. We then use simulations to identify a
 small number of simple simulation rules governing the question-answer 
dynamic in the network. These simple rules not only replicate the 
structural characteristics and algorithm performance on the empirically 
observed Java Forum, but also allow us to evaluate how other algorithms 
may perform in communities with different characteristics. We believe 
this approach will be fruitful for practical algorithm design and 
implementation for <font class="ScopusTermHighlight">online</font> expertise-sharing communities.</span></div>
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2007</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=5700164250&amp;origin=resultslist">Pedagogy, Culture and Society</a></i>
15
(3)
, pp. 349-366
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<div id="previewAbstract158"><span class="txt">Computer-mediated conferencing has been adopted, particularly for purposes of <font class="ScopusTermHighlight">online</font>
 course provision, as a method that can deliver community. Widespread 
interest in a communities-of-practice approach within both informal and 
formal learning has strengthened perceptions of the value of creating a 
community <font class="ScopusTermHighlight">online</font>. A case study 
of asynchronous computer conferencing for the purposes of leadership 
development in schools is the focus for a study of the features and the 
discursive quality of the <font class="ScopusTermHighlight">online</font> interaction that occurred. Two analytical approaches are used: discourse analysis and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 These highlighted different aspects of the case, in terms of the role 
of peers versus the expert moderator (or 'hotseat guest'), the extent of
 readership versus contribution and the tone and content of the 
discussion. Evidence that contributors were learning from the 
interaction was identified and strong links with place-based communities
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 interaction could not be said to constitute a community or to be 
evidently developing in that direction. Its features as a network, where
 weak links were key to a sharing and knowledge-construction process, 
were more salient. Networks offer the potential for weak connections 
that have a particular value for connecting across dispersed 
practitioners and potentially bridging between communities of practice 
and other forms of organisation and groupings. © 2007 Pedagogy, Culture 
&amp; Society.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7403937162&amp;zone=" title="Show author details">Cho, H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=24786770000&amp;zone=" title="Show author details">Gay, G.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402965607&amp;zone=" title="Show author details">Davidson, B.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35609935300&amp;zone=" title="Show author details">Ingraffea, A.</a>
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2007</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=17645&amp;origin=resultslist">Computers and Education</a></i>
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<div id="previewAbstract159"><span class="txt">The aim of this study is 
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styles, social networks, and learning performance in a 
computer-supported collaborative learning (CSCL) community. Using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) and longitudinal survey data, we analyzed how 31 distributed 
learners developed collaborative learning social networks, when they had
 work together on the design of aerospace systems using <font class="ScopusTermHighlight">online</font>
 collaboration tools. The results showed that both individual and 
structural factors (i.e., communication styles and a pre-existing 
friendship network) significantly affected the way the learners 
developed collaborative learning social networks. More specifically, 
learners who possessed high willingness to communicate (WTC) or occupied
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network linkages. We also found that the resultant social network 
properties significantly influenced learners' performance to the extent 
that central actors in the emergent collaborative social network tended 
to get higher final grades. The study suggests that communication and 
social networks should be central elements in a distributed learning 
environment. We also propose that the addition of personality theory 
(operationalized here as communication styles) to structural analysis 
(SNA) contributes to an enhanced picture of how distributed learners 
build their social and intellectual capital in the context of CSCL. © 
2005 Elsevier Ltd. All rights reserved.</span></div>
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<div id="previewAbstract160"><span class="txt">We examine the problem of
 identifying, measuring and evaluating communities in blogs. In our 
approach, we use sense of community (McMillan and Chavis, 1986) and 
centrality measures derived from <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>. We then describe a method for identifying communities in blogs using both sense of community measurement and <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA). We apply this framework to a blog on Canadian independent music.
 Hypotheses are developed concerning the specific structural properties 
of social networks formed by blogging relationships and how those 
properties are related to the sense of community experienced by the 
participants (authors and readers of the blogs). Finally, we discuss the
 implications for blog implementation and use. Copyright © 2007 
Inderscience Enterprises Ltd.</span></div>
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<div id="previewAbstract161"><span class="txt">In addition to science citation indicators of journals like impact and immediacy, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 provides a set of centrality measures like degree, betweenness, and 
closeness centrality. These measures are first analyzed for the entire 
set of 7,379 journals included in the Journal Citation Reports of the 
Science Citation Index and the Social Sciences Citation Index 2004 
(Thomson ISI, Philadelphia, PA), and then also in relation to local 
citation environments that can be considered as proxies of specialties 
and disciplines. Betweenness centrality is shown to be an indicator of 
the interdisciplinarity of journals, but only in local citation 
environments and after normalization; otherwise, the influence of degree
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<div id="previewAbstract162"><span class="txt">Word of mouth (WOM) communication is a major part of <font class="ScopusTermHighlight">online</font> consumer interactions, particularly within the environment of <font class="ScopusTermHighlight">online</font> communities. Nevertheless, existing (offline) theory may be inappropriate to describe <font class="ScopusTermHighlight">online</font> WOM and its influence on evaluation and purchase.The authors report the results of a two-stage study aimed at investigating <font class="ScopusTermHighlight">online</font> WOM: a set of in-depth qualitative interviews followed by a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> of a single <font class="ScopusTermHighlight">online</font>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=35614767800&amp;zone=" title="Show author details">Kidane, Y.H.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7004661333&amp;zone=" title="Show author details">Gloor, P.A.</a>
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2007</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=145592&amp;origin=resultslist">Computational and Mathematical Organization Theory</a></i>
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<div id="previewAbstract165"><span class="txt">This paper studies the temporal communication patterns of <font class="ScopusTermHighlight">online</font>
 communities of developers and users of the open source Eclipse Java 
development environment. It measures the productivity of each community 
and seeks to identify correlations that exist between group 
communication characteristics and productivity attributes. The study 
uses the TeCFlow (Temporal Communication Flow) visualizer to create 
movie maps of the knowledge flow by analyzing the publicly accessible 
Eclipse developer mailing lists as an approximation of the social 
networks of developers and users. Thirty-three different Eclipse 
communities discussing development and use of components of Eclipse such
 as the Java Development Tools, the different platform components, the 
C/ C++ Development Tools and the AspectJ extension have been analyzed 
over a period of six months. The temporal evolution of social network 
variables such as betweenness centrality, density, contribution index, 
and degree have been computed and plotted. Productivity of each 
development group is measured in terms of two indices, namely 
performance and creativity. Performance of a group is defined as the 
ratio of new bugs submitted compared with bugs fixed within the same 
period of time. Creativity is calculated as a function of new features 
proposed and implemented. Preliminary results indicate that there is a 
correlation between attributes of social networks such as density and 
betweenness centrality and group productivity measures in an open source
 development community. We also find a positive correlation between 
changes over time in betweenness centrality and creativity, and a 
negative correlation between changes in betweenness centrality and 
performance. © Springer Science + Business Media, LLC 2006.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7006073763&amp;zone=" title="Show author details">Chau, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8963142900&amp;zone=" title="Show author details">Xu, J.</a>
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2007</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=12960&amp;origin=resultslist">International Journal of Human Computer Studies</a></i>
65
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<div id="previewAbstract166"><span class="txt">Blogs, often treated as the equivalence of <font class="ScopusTermHighlight">online</font>
 personal diaries, have become one of the fastest growing types of 
Web-based media. Everyone is free to express their opinions and emotions
 very easily through blogs. In the blogosphere, many communities have 
emerged, which include hate groups and racists that are trying to share 
their ideology, express their views, or recruit new group members. It is
 important to analyze these virtual communities, defined based on 
membership and subscription linkages, in order to monitor for activities
 that are potentially harmful to society. While many Web mining and 
network analysis techniques have been used to analyze the content and 
structure of the Web sites of hate groups on the Internet, these 
techniques have not been applied to the study of hate groups in blogs. 
To address this issue, we have proposed a semi-automated approach in 
this research. The proposed approach consists of four modules, namely 
blog spider, information extraction, network analysis, and 
visualization. We applied this approach to identify and analyze a 
selected set of 28 anti-Blacks hate groups (820 bloggers) on Xanga, one 
of the most popular blog hosting sites. Our analysis results revealed 
some interesting demographical and topological characteristics in these 
groups, and identified at least two large communities on top of the 
smaller ones. The study also demonstrated the feasibility in applying 
the proposed approach in the study of hate groups and other related 
communities in blogs. © 2006 Elsevier Ltd. All rights reserved.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15128165900&amp;zone=" title="Show author details">Tomsic, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602701410&amp;zone=" title="Show author details">Suthers, D.D.</a>
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2006</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=18405&amp;origin=resultslist">Educational Technology and Society</a></i>
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the social network structure of booking officers at the Honolulu Police 
Department and how the introduction of an <font class="ScopusTermHighlight">online</font>
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 Baseline data provided evidence for collaboration among officers in the
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 minimal collaboration between officers in different districts. On 
average, knowledge of the booking module was low. After introduction of 
the <font class="ScopusTermHighlight">online</font> discussion tool the 
social network structure changed, showing an increase in collaboration 
between different districts and an increase in knowledge of the booking 
module, even though frequency of collaboration did not increase 
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snaring in social networks than raw frequency of interaction. This work 
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<i>Learning by Effective Utilization of Technologies: Facilitating 
Intercultural Understanding, Proceeding of the 14th International 
Conference on Computers in Education, ICCE 2006</i>
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<div id="previewAbstract168"><span class="txt">It is a new direction in the research of CSCL to evaluate the process of knowledge building by <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>. This paper introduces the history, definition and roles of <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>, and explains the methods to evaluate the process of knowledge building in CSCL by measures of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.</span></div>
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1169
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<a href="http://www.scopus.com/record/display.url?eid=2-s2.0-84859081930&amp;origin=resultslist&amp;sort=plf-f&amp;src=s&amp;st1=%22social+network+analysis%22+AND+online&amp;nlo=&amp;nlr=&amp;nls=&amp;sid=F24707DC9D3767AFFD5F36FE052141BF.CnvicAmOODVwpVrjSeqQ%3a20&amp;sot=b&amp;sdt=b&amp;sl=51&amp;s=TITLE-ABS-KEY%28%22social+network+analysis%22+AND+online%29&amp;relpos=1168&amp;relpos=168&amp;searchTerm=TITLE-ABS-KEY%28%5C%26quot%3Bsocial+network+analysis%5C%26quot%3B+AND+online%29" onclick="javascript:submitRecord('2-s2.0-84859081930','168','0');">Application of Social Network Analysis: An approach towards project success and client satisfaction</a>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=36678735300&amp;zone=" title="Show author details">El-Sheikh, A.</a>
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2006</div>
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<i>COBRA 2006 - Proceedings of the Annual Research Conference of the Royal Institution of Chartered Surveyors</i>
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<div id="previewAbstract169"><span class="txt">Project success is the 
ultimate goal for any project coalition. Success is a result of 
collective actions at all levels of any one project along the entire 
project life cycle. One principal aspect of success is the project 
network typology. The aim of this paper is to review different 
attributes for project success (success factors, success measures and 
success levels) as part of broader research on project success, client 
satisfaction and project network. The study is carried out through 
simultaneous analysis of project success factors and project network. 
The correlation is established to highlight the significance of project 
network. Gap analysis is considered and <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA) introduced as a tool for analysing project coalition. It is 
concluded that there is no standard panacea for effective project 
management and project success. SNA is a useful tool among others and 
any control mechanism should be agreed by the project coalition. Deep 
understanding of management tools and strong theoretical background are 
essential for successful application. © 2006 RICS, The Bartlett School, 
UCL and the contributors First published.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55056205800&amp;zone=" title="Show author details">Cook, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603867153&amp;zone=" title="Show author details">Siemieniuch, C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7202410527&amp;zone=" title="Show author details">Sinclair, M.</a>
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2006</div>
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<i>Contemporary Ergonomics 2006</i>
, pp. 70-72
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<div id="previewAbstract170"><span class="txt">Appropriate group 
decision-making is considerably influenced by the structure of the 
group. To understand the group arrangement you must look beyond formal 
organizational charts using <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA) to reveal the informal, often hidden, networks. Once the patterns
 of interaction within the group are understood, it is possible to 
intervene to reinforce/alter existing networks or create new patterns. 
The subsequent group structure may be better able to make decisions 
through this shaping.</span></div>
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1171
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2006</div>
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<i>Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006</i>
7
, pp. 4093-4100
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<div id="previewAbstract171"><span class="txt">The resource-based view 
(RBV) considers organizational routines as fundamental for IT value 
creation as they determine the efficiency with which firms transform 
inputs to outputs. Yet, our understanding of how routines affect firm 
performance is still incomplete, especially concerning the contribution 
and complementarities between IT and non-IT-resources. As routines 
involve humans and consist of more than just technical aspects, we 
propose to use methods of <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 (SNA) to formalize the social aspects of routines. We extend central 
findings of the RBV by considering the impact of the social embeddedness
 of a firm's employees using Granovetter's strength of ties argument. By
 considering RBV and SNA perspectives, we develop a model regarding the 
role of routines for alignment explaining how and why routines are able 
to generate positive outcomes of IT. The model provides good support for
 the effects cited in the literature and is illustrated by a case.</span></div>
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2006</div>
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<i>Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006</i>
7
, pp. 3961-3964
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<div id="previewAbstract172"><span class="txt">In this study, we look at beginning to explore roles and how individuals fill those roles in face-to-face and <font class="ScopusTermHighlight">online</font>
 social networks. The long term goal of the research is to be able to 
map both the roles and the individuals as they move between the two 
types of social networks. The mapping of this migration will provide 
community administrators with tools and knowledge that can be used to 
better support the community members. This paper presents the results of
 a pilot study that explored the feasibility of an approach to carry out
 this research. A learning environment is studied that utilizes a mixed 
mode approach, using both the classroom and <font class="ScopusTermHighlight">online</font> bulletin boards. Through the use of observation, content analysis, surveys and interviews, classroom and <font class="ScopusTermHighlight">online</font>
 roles are discovered and the beginnings of a meaningful mapping of 
those roles and how individuals fill them is uncovered. Finally our 
modified approach is presented as the full study is getting underway.</span></div>
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2006</div>
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<i>Conferences in Research and Practice in Information Technology Series</i>
61
, pp. 185-190
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<div id="previewAbstract173"><span class="txt">Internet based <font class="ScopusTermHighlight">online</font>
 social networks collectively facilitate the spread of ideas. Hence, to 
understand how social networks evolve as a function of time, it is 
critical to learn the relationship between the information dissemination
 pathways or flows and the type of ideas being disseminated. We first 
classify the spread of ideas into two types based on their rate and 
nature of proliferation; fads and non-fads. A 'fad' refers to an idea 
that quickly becomes popular in a culture, remains popular for a brief 
period, and then loses popularity dramatically. We then model the 
information dissemination pathways for both these types of ideas. Our 
results indicate that the proliferation of information in a network 
strongly correlates with the the type of idea, the degree of 
participation of the nodes, and a node's availability i.e., presence. 
Further we derived that after reaching a certain saturation point, a fad
 exhibits periodic spreading behavior implying that a fad rarely 
completely disappears from a network. We use data from an instant 
messaging network community to verify the proposed theoretical modeling 
framework. © 2006, Australian Computer Society, Inc.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7405878842&amp;zone=" title="Show author details">Sharma, S.K.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55493814400&amp;zone=" title="Show author details">Xu, H.</a>
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2006</div>
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<i>Proceedings - 2006 10th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2006</i>
, art. no. 4019260
, pp. 1258-1262
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<div id="previewAbstract174"><span class="txt">Virtual Communities have 
become an important aspect in the world of e-commerce. Interactions and 
product recommendations are increasingly employed by several <font class="ScopusTermHighlight">online</font>
 businesses. This study examines diverse case studies for the 
understanding of how virtual communities operate and exchange 
information, and whether these social interactions influence business 
sales and relationships. The findings of a web based e-mail 
questionnaire survey, interview responses and discussions commissioned 
are reported in this paper. ©2006 IEEE.</span></div>
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<i>2006 2nd International Conference on Semantics Knowledge and Grid, SKG</i>
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<div id="previewAbstract175"><span class="txt">In this paper, we propose a user reputation model and use it for a user-interactive question answering system. It combines the <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> approach and the user rating approach. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 is applied to analyze the impact of participant users ' relations to 
their reputations. User rating is used to acquire direct judgment of a 
user's reputation based on other users' experiences with this user. 
Preliminary experiments show that the computed reputations based on our 
proposed reputation model can reflect the actual reputations of the 
simulated roles and therefore can fit well in our user-interactive 
question answering system. © 2006 IEEE.</span></div>
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<i>Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006</i>
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, pp. 4037-4044
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<div id="previewAbstract176"><span class="txt">This contribution 
presents a modeling approach for describing social issues in knowledge 
organizations. Social issues are one key factor in knowledge 
organizations for its business success. In the first part, a knowledge 
organization is described as a socio-technical system with heterarchic 
structures. Then modes for exploring social structures using <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
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applications in knowledge management deficiencies of a pure SNA approach
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modeling knowledge organizations is introduced.</span></div>
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<i>ACIS 2006 Proceedings - 17th Australasian Conference on Information Systems</i>
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<div id="previewAbstract178"><span class="txt"><font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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it is difficult to comprehend the characteristics and structure of 
networks when there are many edges and nodes, and (2) current systems 
are often a medley of statistical methods and overwhelming visual output
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 manner. This results in exploration that is largely opportunistic. The 
contributions of our work are principles and an interface to support 
systematic analysis of social networks. We believe our approach will 
enable users to better understand the structure of networks and the 
social groups within.</span></div>
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<div id="previewAbstract179"><span class="txt">The knowledge of an 
organization's employees is a valuable asset. Therefore organizations 
should ensure that their employees share their knowledge among each 
other. Knowledge exchanges between employees can be modelled as a 
network of relationships. To study these networks we have developed the 
Knowledge Network Analysis technique, which is based on <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font>
 and supports visual as well as quantitative analysis of knowledge 
networks. The goal of this technique is to identify bottlenecks in 
knowledge sharing in a particular knowledge area. In this paper we 
present the results of the application of Knowledge Network Analysis in 
an explorative case study. The goal of the case study is to explore the 
usefulness of Knowledge Network Analysis in identifying knowledge 
sharing bottlenecks. The case study results in a deeper understanding of
 how to translate the characteristics of the knowledge network and the 
employees in this network to the context of the case study organization.
 Moreover, the case study results have also been used to formulate 
recommendations to improve knowledge sharing at the case study 
organization.</span></div>
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<div id="previewAbstract180"><span class="txt">Open Source Software 
(OSS) projects provide a unique opportunity to gather and analyze 
publicly available historical data. The Postgres SQL server, for 
example, has over seven years of recorded development and communication 
activity. We mined data from both the source code repository and the 
mailing list archives to examine the relationship between communication 
and development in Postgres. Along the way, we had to deal with the 
difficult challenge of resolving email aliases. We used a number of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> measures and statistical techniques to analyze this data. We present our findings in this paper.</span></div>
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<i>ICIS 2006 Proceedings - Twenty Seventh International Conference on Information Systems</i>
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<div id="previewAbstract181"><span class="txt">Identity crisis has been a
 longstanding problem for the Information Systems (IS) community. Most 
previous studies have addressed this problem from the philosophical 
perspective, but few have tackled it from the social network 
perspective. In this paper, we report our work on studying the social 
identity of IS by applying <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 on the collaboration (co-authorship) network for ICIS papers over the 
past 26 years. The social network of IS researchers and the 
characteristics of the network were identified and discussed. Our 
results showed that the IS community is well connected and has 
demonstrated frequent interactions among members. The critical mass of 
the community, the most productive authors and institutions, was 
identified. Cross-institutional collaboration patterns were also 
studied, and some interesting results were revealed. In addition, we 
studied how the social network has evolved over time. The networks at 
three different time periods were constructed and compared. We found 
that the network has evolved healthily over time with the addition of 
new members and the improved connection among members. Overall, our 
analyses indicated that the IS community has maintained the social 
identity well and we expect the trend to keep on in the future.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55497694600&amp;zone=" title="Show author details">Long, Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=55502430500&amp;zone=" title="Show author details">Siau, K.</a>
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2006</div>
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<i>Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006</i>
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, pp. 810-820
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<div id="previewAbstract182"><span class="txt">Drawing on social network
 theories and previous studies, this research is an initial effort to 
explore the dynamics of the social network structure in Open Source 
Software (OSS) teams. Three projects were selected from SourceForge.net 
in term of their similarities as well as their differences. Monthly data
 were extracted from the bug tracking system in order to achieve a 
longitudinal view of the interaction pattern of each project. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 was used to generate the indices of network structure. The finding 
suggests that the interaction pattern of OSS projects evolves from a 
single hub at the beginning to a core/periphery model as the projects 
move forward.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7004661333&amp;zone=" title="Show author details">Gloor, P.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8240063900&amp;zone=" title="Show author details">Paasivaara, M.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602140901&amp;zone=" title="Show author details">Schoder, D.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=18839527500&amp;zone=" title="Show author details">Willems, P.</a>
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2006</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=4900153501&amp;origin=resultslist">IFIP International Federation for Information Processing</a></i>
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, pp. 265-272
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<div id="previewAbstract183"><span class="txt">Teaching a course on optimizing <font class="ScopusTermHighlight">online</font> communication behavior and <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> permitted us to obtain preliminary results on correlating temporal <font class="ScopusTermHighlight">online</font>
 communication patterns with team performance. Students from Helsinki 
University of Technology and University of Cologne who had never met 
face to face formed virtual interdisciplinary teams collaborating on a 
common task. While collaborating over long distance, students kept track
 of their own communication activities by e-mail, chat, and conference 
calls with Skype. The contribution of this paper is twofold. First, we 
introduce an innovative course format creating an empirical base for 
team performance in a distributed <font class="ScopusTermHighlight">online</font>
 communication environment. Secondly, we provide basic analysis of 
correlations between SNA measures and team performance. Students used 
these insights to optimize their own communication behavior for future 
virtual collaboration.</span></div>
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<i>Proceedings of the 14th European Conference on Information Systems, ECIS 2006</i>
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<div id="previewAbstract184"><span class="txt">In this paper we propose a
 model to analyze community dynamics. Recently, several methods and 
tools have been proposed to extract communities from static graphs. 
However, since communities are not static, but change over time, it is 
necessary to provide methods to determine and observe the community 
transitions and to extract the factors that cause the development. We 
regard a community as an object that exists over time and propose to 
observe community transitions along the time axis. For this we partition
 the time axis under observation by time windows. In each time window, a
 set of interactions between community participants is aggregated. These
 static networks are analyzed for subcommunities by applying community 
detection mechanisms. Through this we detect communities in each 
interval and can observe if communities persist over time or undergo a 
transition. We present community transitions and the observable 
indicators for the respective development. We furthermore present a 
software environment that incorporates several community detection and 
analysis methods to analyze community transitions. It supports a dynamic
 temporal community analysis and provides several forms of 
visualizations and analysis settings thus providing an interactive tool 
to observe community dynamics.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=18634019100&amp;zone=" title="Show author details">Hossain, L.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=17347334900&amp;zone=" title="Show author details">Wu, A.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=16635165900&amp;zone=" title="Show author details">Choi, B.</a>
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2006</div>
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<i>ICIS 2006 Proceedings - Twenty Seventh International Conference on Information Systems</i>
, pp. 1175-1198
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<div id="previewAbstract185"><span class="txt">In this study, we explore
 the correlation between actor centrality and project based 
coordination. By drawing from established coordination and 
organisational process theory, a text-mining tool is designed and 
implemented to measure coordination from a large dataset of emails. 
Here, we provide effective mechanisms for: (i) cataloguing coordination 
key phrases from an email corpus; (ii) the calculation of coordination 
score based on project scope; (iii) the construction of social network 
matrices using centrality measures, and (iv) approaches for exploring 
the association between network centrality and coordination score. We 
argue that actor centrality affects the ability of an individual to 
coordinate the actions of others. The following questions guide this 
study--What is the effect of network centrality on organisational 
coordination? How is the actor's ability to coordinate projects related 
to their structural position in the communications network? We developed
 multi-layered test designs to explore this relationship in a 
project-based (macro) and cross-project (micro) level. We suggest four 
major findings from the analysis of communication data from Enron email 
corpus. Firstly, it is concluded that centrally positioned actors show 
more coordinative activity. Secondly, it is found that betweenness index
 of centrality is the most potent predicate for coordination. Thirdly, 
the influence of an actor is associated with coordination more so than 
the actor's prominence. Lastly, results suggest that coordination 
ability is more closely correlated to actor centrality than the 
organisational position. It is therefore concluded that centrally 
'well-connected' people are able to exercise greater coordination within
 the network structure.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7501950297&amp;zone=" title="Show author details">Chen, C.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14827062700&amp;zone=" title="Show author details">Panjwani, G.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=8899578600&amp;zone=" title="Show author details">Proctor, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603559726&amp;zone=" title="Show author details">Allendoerfer, K.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6701390963&amp;zone=" title="Show author details">Kuljis, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14826307000&amp;zone=" title="Show author details">Aluker, S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14827100900&amp;zone=" title="Show author details">Sturtz, D.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=14827560700&amp;zone=" title="Show author details">Vukovic, M.</a>
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2006</div>
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<i>People and Computers XIX - The Bigger Picture, Proceedings of HCI 2005</i>
, pp. 233-250
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<div id="previewAbstract186"><span class="txt">A study of the evolution 
of the HCI community is described based on information extracted from 
leading HCI journals. The study includes a traditional author 
co-citation analysis and a progressive domain visualization of a 
co-authorship network of 3,620 authors and a 1,038-node hybrid network 
of topical terms and cited articles. Emerging trends and prominent 
patterns of these networks are identified and compared with an existing 
survey of the field. The study contributes to the understanding of HCI 
at a macroscopic level as well as to the improvement of methodological 
implications.</span></div>
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1187
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7006780913&amp;zone=" title="Show author details">Verbeek, H.M.W.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602091082&amp;zone=" title="Show author details">Van Dongen, B.F.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6503908779&amp;zone=" title="Show author details">Mendling, J.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7007153024&amp;zone=" title="Show author details">Van Der Aalst, W.M.P.</a>
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2006</div>
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<i>CEUR Workshop Proceedings</i>
200
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0
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<div id="previewAbstract187"><span class="txt">Originally the ProM 
framework was developed as a design artifact for the process mining 
domain, i.e., extracting process models from event logs. However, in 
recent years the scope of the framework has become broader and now 
includes process verification, <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 conformance checking, verification based on temporal logic, etc. 
Moreover, the framework supports a wide variety of process models, e.g.,
 Petri nets, Event-driven Process Chains (EPCs), Heuristics nets, YAWL 
models, and is plug-able, i.e., people can add plug-ins without changing
 the framework itself. This makes the ProM framework an interesting 
environment for model interoperability. For example, people can take 
transaction log from IBM's WebSphere, discover a process model in terms 
of a heuristics net, convert the heuristics net to a Petri net for 
analysis, load an EPC defined using the ARIS toolset, verify the EPC and
 convert it to a Petri net, determine the fitness of the ARIS model 
given the transaction log from WebSphere, and finally convert both 
models to a YAWL specification that is exported. Such application 
scenarios are supported by ProM and demonstrate true model 
interoperability. In this paper, we present ProM's interoperability 
capabilities using a running example.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=15047335400&amp;zone=" title="Show author details">Zhou, Y.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7405963529&amp;zone=" title="Show author details">Davis, J.</a>
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2006</div>
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<i>Proceedings of the 15th International Conference on World Wide Web</i>
, pp. 1017-1018
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<div id="previewAbstract188"><span class="txt">Weblog has quickly 
evolved into a new information and knowledge dissemination channel. Yet 
it is not easy to discover weblog communities through keyword search. 
The main contribution of this paper is the study of weblog communities 
from the perspective of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>.
 We proposed a new way of collecting and preparing data for weblog 
community discovery. The data collection stage focuses on gaining 
knowledge of the strength of social ties between weblogs. The strength 
of social ties and the clustering feature of social network guided the 
discovery of weblog communities.</span></div>
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2006</div>
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<i>Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006</i>
7
, pp. 4068-4072
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0
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<div id="previewAbstract189"><span class="txt">A key question for 
managers in knowledge-intensive firms is how to encourage knowledge 
flows and new knowledge creation between individuals. Research has 
demonstrated that relationships are critical to knowledge exchange, yet 
we know little about the specific characteristics of relationships that 
affect access to different types of knowledge. Additionally, while prior
 research has focused on relationships based on face-to-face 
communication, with advances in information and communications 
technologies, individuals can just as easily seek knowledge through 
computer-mediated communication, changing the nature of the 
relationships that facilitate knowledge exchange. Therefore, our quest 
is to better understand how technology influences knowledge exchange, 
how the attributes of the relationships between individuals influence 
knowledge exchange, and how having access to different types of 
knowledge affects individual performance in organizations. Data will be 
gathered and analyzed in network form, using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> techniques. Structural equation modeling will be used to test the hypothesized path model.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6604054547&amp;zone=" title="Show author details">Contractor, N.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=9941929100&amp;zone=" title="Show author details">Hesse, B.W.</a>
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2006</div>
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<i>ACM International Conference Proceeding Series</i>
151
, pp. 9-10
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<div id="previewAbstract190"><span class="txt">Peter Schad will begin 
the symposium with a description of the vision and architecture 
underlying the National Cancer Institute's cancer Biomedical Informatics
 Grid, or caBIG?. The caBIG architecture is designed to bring the 
terabytes and petabytes of data being produced in cancer research onto a
 common, interoperable platform to enhance discovery, development, and 
delivery in the national program's war on cancer. Stephen Marcus will 
describe how the NCI is exploring the use of cyberinfrastructure to 
connect data from relevant cancer surveillance systems into a seamless 
thread of support for public health researchers, policy makers, and 
public health administrators. Dr. Marcus will explain how the NCI has 
been making data from its nationally representative Health Information 
National Trends Survey (HINTS) available to communication researchers 
through an <font class="ScopusTermHighlight">online</font> 
collaboratory, and he will describe plans to link national data systems 
on tobacco use to improve the effectiveness and reach of public health 
surveillance. Shu-Hong Zhu will offer an example of how large scale 
databases and metadata repositories can be used to enable research on 
data collected through a national consortium of publicly funded " 
Quitlines" for smokers. Because smoking-related cancers kill more 
Americans than any other cancer, increasing the reach and effectiveness 
of cessation resources must remain a public health priority. Creating a 
cyberinfrastructure to connect here-to-fore disparate data systems 
should elevate the precision of scientific analysis in the area of 
Quitline research from a local to a national level. Noshir Contractor, a
 current digital government grantee, will present a blueprint for 
connecting public health researchers through a distributed network of 
people, data, and resources in the area of public health surveillance 
and evaluation. Building on his work in <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>,
 Dr. Contractor will illustrate how members of a geographically 
distributed community of population scientists can use networked 
connections to shorten the time it takes to identify, and respond more 
efficiently and effectively to, public health perturbations. Patty Mabry
 will complete the symposium by offering a glimpse of efforts underway 
to connect the biomedical research efforts supported by the National 
Institutes of Health (NIH) with the advanced computing initiatives 
sponsored by the National Science Foundation. Dr. Mabry, who works in 
the NIH Office of Behavioral and Social Science Research, is working 
with NIH leaders to improve knowledge management and to shorten 
time-to-discovery through cyberinfrastructure in the fields of 
biomedicine and public health.</span></div>
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2006</div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=21368&amp;origin=resultslist">Instructional Science</a></i>
34
(6)
, pp. 451-480
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<div id="previewAbstract191"><span class="txt"><font class="ScopusTermHighlight">Online</font>
 discussion plays a unique role in face-to-face and distance teaching 
and learning. Interaction and student cognitive engagement during the <font class="ScopusTermHighlight">online</font>
 discussion are critical for constructing new understanding and 
knowledge. This article analyzes types of interaction that occur during <font class="ScopusTermHighlight">online</font>
 discussions, examines levels of student cognitive engagement in each 
discussion, and explores their effects on and implications for learning 
and teaching in higher education. By combining methods of <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 with qualitative content analysis, the article explores new 
methodologies for analyzing participation, interaction, and learning 
that take place <font class="ScopusTermHighlight">online</font>, and suggests areas for research in learning and teaching <font class="ScopusTermHighlight">online</font>. © Springer 2006.</span></div>
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<i>Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval</i>
2006
, pp. 210-211
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<div id="previewAbstract192"><span class="txt">The role of network 
structure has grown in significance over the past ten years in the field
 of information retrieval, stimulated to a great extent by the 
importance of link analysis in the development of Web search techniques 
[4]. This body of work has focused primarily on the network that is most
 clearly visible on the Web: the network of hyperlinks connecting 
documents to documents. But the Web has always contained a second 
network, less explicit but equally important, and this is the social 
network on its users, with latent person-to-person links encoding a 
variety of relationships including friendship, information exchange, and
 influence. Developments over the past few years - including the 
emergence of social networking systems and rich social media, as well as
 the availability of large-scale e-mail and instant messenging datasets -
 have highlighted the crucial role played by on-line social networks, 
and at the same time have made them much easier to uncover and analyze. 
There is now a considerable opportunity to exploit the information 
content inherent in these networks, and this prospect raises a number of
 interesting research challengesWithin this context, we focus on some 
recent efforts to formalize the problem of searching a social network. 
The goal is to capture the issues underlying a variety of related 
scenarios: a member of a social networking system such as MySpace seeks a
 piece of information that may be held by a friend of a friend [27, 28];
 an employee in a large company searches his or her network of 
colleagues for expertise in a particular subject [9]; a node in a 
decentralized peer-to-peer file-sharing system queries for a file that 
is likely to be a small number of hops away [2, 6, 16, 17]; or a user in
 a distributed IR or federated search setting traverses a network of 
distributed resources connected by links that may not just be 
informational but also economic or contractual [3, 5, 7, 8, 13, 18, 21].
 In their most basic forms, these scenarios have some essential features
 in common: a node in a network, without global knowledge, must find a 
short path to a desired "target" node (or to one of several possible 
target nodes). To frame the underlying problem, we go back to one of the
 most well-known pieces of empirical <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 - Stanley Milgram's research into the small-world phenomenon, also 
known as the "six degrees of separation" [19, 24, 25]. The form of 
Milgram's experiments, in which randomly chosen starters had to forward a
 letter to a designated target individual, established not just that 
short chains connecting far-flung pairs of people are abundant in large 
social networks, but also that the individuals in these networks, 
operating with purely local information about their own friends and 
acquaintances, are able to actually find these chains [10]. The Milgram 
experiments thus constituted perhaps the earliest indication that 
large-scale social networks are structured to support this type of 
decentralized search. Within a family of random-graph models proposed by
 Watts and Strogatz [26], we have shown that the ability of a network to
 support this type of decentralized search depends in subtle ways on how
 its "long-range" connections are correlated with the underlying spatial
 or organizational structure in which it is embedded [10, 11]. Recent 
studies using data on communication within organizations [1] and the 
friendships within large on-line communities [15] have established the 
striking fact that real social networks closely match some of the 
structural features predicted by these mathematical models. If one looks
 further at the on-line settings that provide the initial motivation for
 these issues, there is clearly interest from many directions in their 
long-term economic implications - essentially, the consequences that 
follow from viewing distributed information retrieval applications, 
peer-to-peer systems, or social-networking sites as providing 
marketplaces for information and services. How does the problem of 
decentralized search in a network change when the participants are not 
simply agents following a fixed algorithm, but strategic actors who make
 decisions in their own self-interest, and may demand compensation for 
taking part in a protocol? Such considerations bring us into the realm 
of algorithmic game theory, an active area of current research that uses
 game-theoretic notions to quantify the performance of systems in which 
the participants follow their own self-interest [20, 23]. In a simple 
model for decentralized search in the presence of incentives, we find 
that performance depends crucially on both the rarity of the information
 and the richness of the network topology [12] - if the network is too 
structurally impoverished, an enormous investment may be required to 
produce a path from a query to an answer.</span></div>
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<a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=7402755585&amp;zone=" title="Show author details">Choi, B.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6603924681&amp;zone=" title="Show author details">Raghu, T.S.</a>, <a href="http://www.scopus.com/authid/detail.url?origin=resultslist&amp;authorId=6602142704&amp;zone=" title="Show author details">Vinze, A.</a>
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2006</div>
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<i>Proceedings of the Annual Hawaii International Conference on System Sciences</i>
6
, art. no. 1579571
, pp. 139a
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<div id="previewAbstract193"><span class="txt">Research on the nature of
 e-business standards and the organizational context in which they are 
developed has received little attention in the literature of IT 
standards and standardization. This study investigates communication 
patterns in <font class="ScopusTermHighlight">online</font> standards 
groups to provide insights into the nature of group dynamics among 
standards decision makers and its relation to the standards context. 
Email data is used from the ebXML standards initiative. Findings suggest
 that standards groups operating on the Internet appear to form a 
cohesive structure, despite the fact that they tend to consist of large 
group of participants coming from various backgrounds and industries, 
while their communication patterns are influenced by standards 
orientation. Policy implications for managers in <font class="ScopusTermHighlight">online</font> standards groups are presented. © 2006 IEEE.</span></div>
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2006</div>
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<i>Proceedings of the Annual Hawaii International Conference on System Sciences</i>
3
, art. no. 1579410
, pp. 59b
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<div id="previewAbstract194"><span class="txt">Understanding the social 
roles of the members a group can help to understand the social context 
of the group. We present a method of applying <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
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and newsgroups. Results show that newsgroups vary in terms of the 
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authors. © 2006 IEEE.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=26199&amp;origin=resultslist">ACM Transactions on Computer-Human Interaction</a></i>
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<div id="previewAbstract195"><span class="txt">This article presents an analysis of the human to human interactions in two public <font class="ScopusTermHighlight">online</font>
 newsgroups, one targeting the young generation and the other the 
elderly. The main goal of this study was to establish a better 
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 among the participants of these two newsgroups. A series of 
analytical/statistical techniques, like <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">Network</font> <font class="ScopusTermHighlight">Analysis</font> (SNA), were used in order to get a better understanding of the <font class="ScopusTermHighlight">online</font>
 communities that have emerged around the participants of these two 
newsgroups. The SNA analysis showed that the teens newsgroup is more 
highly connected, has more messages sent and received and has a higher 
reciprocity. On the other hand, the senior newsgroup has more central 
dominant people who tend to make the rest of the network dependent on 
them for communication. © 2006 ACM.</span></div>
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=40067&amp;origin=resultslist">Proceedings of SPIE - The International Society for Optical Engineering</a></i>
6201
, art. no. 620105
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tracking of embedded malicious subnets in an active social network can 
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generated in the natural interaction of large numbers of actors 
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<i><a href="http://www.scopus.com/source/sourceInfo.url?sourceId=25674&amp;origin=resultslist">Lecture
 Notes in Computer Science (including subseries Lecture Notes in 
Artificial Intelligence and Lecture Notes in Bioinformatics)</a></i>
3942 LNCS
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<div id="previewAbstract197"><span class="txt">The ability to better 
understand role performing during the learning process of a 
collaborative learning team is very crucial, in order to effectively 
support <font class="ScopusTermHighlight">online</font> students. 
Leadership roles which have the most influence in directing the team 
should be carefully recognized. Identifying the emergent team leaders is
 challenging because these roles are normally distributed and shifted 
among team members over time. In this paper, a new approach for the 
leadership roles identification is, thus proposed. The collaboration 
patterns are examined with different points of social network views to 
discover the network locations of the leaders. The proposed leadership 
index is a combination of degree of centrality, closeness and 
betweenness. The experiment and the simulation results indicate that the
 proposed index is promising. © Springer-Verlag Berlin Heidelberg 2006.</span></div>
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64
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<div id="previewAbstract198"><span class="txt">Evaluating on-line 
collaborative learning interactions is a complex task due to the variety
 of elements and factors that take place and intervene in the way a 
group of students comes together to collaborate in order to achieve a 
learning goal. The aim of this paper is to provide a better 
understanding of group interaction and determine how to best support the
 collaborative learning process. To that end, we propose a principled 
framework for the study and analysis of group interaction and group 
scaffolding which is built by combining different aspects and issues of 
collaboration, learning and evaluation. In particular, we define 
learning activity indicators at several levels of description which 
prompt to the application of a mixed interaction analysis scheme and the
 use of different data types and specific tools. At an initial layer, 
the basis of the approach is set by applying a qualitative process for 
evaluating the individual and group task performance as well as the 
group functioning and scaffolding. The interaction analysis process is 
completed by defining and applying two more layers: a <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 of the group activity and participation behaviour and a quantitative 
analysis of group effectiveness as regards task achievement and active 
interaction involvement. Our work defines a grounded and holistic 
conceptual model that describes on-line collaborative learning 
interactions sufficiently and applies it in a real, web-based, complex 
and long-term collaborative learning situation. An in-depth empirical 
evaluation of the conceptual model is fully discussed, which 
demonstrates the usefulness and value of the approach. © 2006 Elsevier 
Ltd. All rights reserved.</span></div>
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<div id="previewAbstract199"><span class="txt">Background: The DSM 
criteria for a delusion indicate that it should not include any beliefs 
held by a person's 'culture or subculture'. The internet has many 
examples of people reporting 'mind control experiences' (MCEs) on 
self-published web pages, many of which suggest a community based around
 such beliefs and experiences. It was hypothesized that some of these 
reports are likely to reflect delusional beliefs and the hyperlinks 
between web reports were likely to show evidence of social structure, 
demonstrating the 'culture or subculture' exemption to be increasingly 
redundant in light of new technology. Sampling and Methods: Texts from 
web sites reporting MCEs (n = 10), experience of cancer (n = 10), 
depression (n = 10) and being stalked (n = 10) were identified, and were
 blind-rated by three independent psychiatrists for the presence of 
delusions. Hyperlinks from web sites reporting MCEs were used to create a
 network structure; this was compared with a size-matched, randomly 
generated network and known social networks from the literature using <font class="ScopusTermHighlight">social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>. Conclusions: The sampled web-published accounts of MCEs are highly likely to be influenced by delusional beliefs. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font> suggests there is significant evidence of an <font class="ScopusTermHighlight">online</font>
 community based around these beliefs. The fact that individuals can 
form a community based on the content of a potentially delusional belief
 presents a paradox for the DSM diagnostic criteria for a delusion, and 
suggests the need to revise and revisit the original operational 
definition in the light of these new technological developments. 
Copyright © 2006 S. Karger AG.</span></div>
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2005</div>
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<i>Proceedings of the European Conference on Knowledge Management, ECKM</i>
, pp. 615-620
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0
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<div id="previewAbstract200"><span class="txt">This research-in-progress
 is concerned with assessing and supporting the role of informal 
networks within an inter-organisational R and D collaboration. <font class="ScopusTermHighlight">Social</font> <font class="ScopusTermHighlight">network</font> <font class="ScopusTermHighlight">analysis</font>
 (SNA) tools have been used to 'map' important networks within 
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the applications of these tools to an inter-organisational collaboration
 context is almost non-existent. In phase 1 of this research, an 
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1, the 2nd phase of this study is concerned with developing a framework 
to promote effective collaboration within an inter-organisational 
network. This framework will be underpinned by complexity theory 
concepts. Many authors have called for the application of complexity 
theories to better understand social networks, yet few authors have 
systematically applied these concepts.</span></div>
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